• Title/Summary/Keyword: use for learning

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A Sensor Data Management System for USN based Fire Detection Application (USN 기반의 화재감시 응용을 위한 센서 데이터 처리 시스템)

  • Park, Won-Ik;Kim, Young-Kuk
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.5
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    • pp.135-145
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    • 2011
  • These days, the research of a sensor data management system for USN based real-time monitoring application is active thanks to the development and diffusion of sensor technology. The sensor data is rapidly changeable, continuous and massive row level data. However, end user is only interested in high level data. So, it is essential to effectively process the row level data which is changeable, continuous and massive. In this paper, we propose a sensor data management system with multi-analytical query function using OLAP and anomaly detection function using learning based classifier. In the experimental section, we show that our system is valid through the some experimental scenarios. For the this, we use a sensor data generator implemented by ourselves.

The Study of Facebook Marketing Application Method: Facebook 'Likes' Feature and Predicting Demographic Information (페이스북 마케팅 활용 방안에 대한 연구: 페이스북 '좋아요' 기능과 인구통계학적 정보 추출)

  • Yu, Seong Jong;Ahn, Seun;Lee, Zoonky
    • The Journal of Bigdata
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    • v.1 no.1
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    • pp.61-66
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    • 2016
  • With big data analysis, companies use the customized marketing strategy based on customer's information. However, because of the concerns about privacy issue and identity theft, people start erasing their personal information or changing the privacy settings on social network site. Facebook, the most used social networking site, has the feature called 'Likes' which can be used as a tool to predict user's demographic profiles, such as sex and age range. To make accurate analysis model for the study, 'Likes' data has been processed by using Gaussian RBF and nFactors for dimensionality reduction. With random Forest and 5-fold cross-validation, the result shows that sex has 75% and age has 97.85% accuracy rate. From this study, we expect to provide an useful guideline for companies and marketers who are suffering to collect customers' data.

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A Study on Attitudes toward Man's Appearance Management and Cosmetics Purchasing Behavior (남성들의 미용에 대한 관심과 화장품 구매행동 연구)

  • Yim, Su-Hyun;Kim, Min-Shin
    • Journal of the Korea Fashion and Costume Design Association
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    • v.16 no.4
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    • pp.79-98
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    • 2014
  • As men are interested in fashion and beauty and invest for himselves nowadays, the scale of men's cosmetic businesses is showing steadily tendency. The purposes of this were to offer data to establish a marketing strategies learning follows: The findings of this study were as follows: First, according to the survey on men's consideration of their look, it showed their high interest in it. 29% respondents carry cosmetics in their hands normally. Second, Men's level of skin management knowledge is quite high according the survey. Third, The largest group of respondents are obtaining information about cosmetics through mass media. therefore, there will be necessity for cosmetic firms to aggressively pursue positive publicity strategy various of mass media. Fourth, Regarding purchasing behavior, 53.2% buy cosmetics in person, who outnumbered the others who don't. In the case of men who don't buy cosmetics by themselves, spouses or girl friends purchase cosmetics on behalf of them. Fifth, as a result of examine the demand level for men's cosmetics, the men, who answered that it is appropriate a lotion and toner is priced between 10,000 won and 30,000 won were the largest with 51.1%. Men who answered that beside the basic cosmetics such as toner and lotion that use, they will purchase sunscreen in the future. Men sho recognize the most important task needed to be improved in men's cosmetics is higher quality, with 25.9%.

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Study of Static Analysis and Ensemble-Based Linux Malware Classification (정적 분석과 앙상블 기반의 리눅스 악성코드 분류 연구)

  • Hwang, Jun-ho;Lee, Tae-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.6
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    • pp.1327-1337
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    • 2019
  • With the growth of the IoT market, malware security threats are steadily increasing for devices that use the linux architecture. However, except for the major malware causing serious security damage such as Mirai, there is no related technology or research of security community about linux malware. In addition, the diversity of devices, vendors, and architectures in the IoT environment is further intensifying, and the difficulty in handling linux malware is also increasing. Therefore, in this paper, we propose an analysis system based on ELF which is the main format of linux architecture, and a binary based analysis system considering IoT environment. The ELF-based analysis system can be pre-classified for a large number of malicious codes at a relatively high speed and a relatively low-speed binary-based analysis system can classify all the data that are not preprocessed. These two processes are supposed to complement each other and effectively classify linux-based malware.

A Simple Stereo Matching Algorithm using PBIL and its Alternative (PBIL을 이용한 소형 스테레오 정합 및 대안 알고리즘)

  • Han Kyu-Phil
    • The KIPS Transactions:PartB
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    • v.12B no.4 s.100
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    • pp.429-436
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    • 2005
  • A simple stereo matching algorithm using population-based incremental learning(PBIL) is proposed in this paper to decrease the general problem of genetic algorithms, such as memory consumption and inefficiency of search. PBIL is a variation of genetic algorithms using stochastic search and competitive teaming based on a probability vector. The structure of PBIL is simpler than that of other genetic algorithm families, such as serial and parallel ones, due to the use of a probability vector. The PBIL strategy is simplified and adapted for stereo matching circumstances. Thus, gene pool, chromosome crossover, and gene mutation we removed, while the evolution rule, that fitter chromosomes should have higher survival probabilities, is preserved. As a result, memory space is decreased, matching rules are simplified and computation cost is reduced. In addition, a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities, like a result of coarse-to-fine matchers. Because of this scheme, the proposed algorithm can produce a stable disparity map with a small fixed-size window. Finally, an alterative version of the proposed algorithm without using probability vector is also presented for simpler set-ups.

An Analysis of the Discourse on the Length Concept in a Classroom for the Length of Space Curve (곡선의 길이 수업에서 길이 개념에 대한 담론 분석)

  • Oh, Taek-Keun
    • School Mathematics
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    • v.19 no.3
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    • pp.571-591
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    • 2017
  • The purpose of this study is to understand the characteristics of mathematical discourse about the length in the class that learns the length of the curve defined by definite integral. For this purpose, this study examined the discourse about length by paying attention to the usage of the word 'length' in the class participants based on the communicative approach. As a result of the research, it was confirmed that the word 'length' is used in three usages - colloquial, operational, and structural usage - in the process of communicating with the discourse participants. Particularly, each participant did not recognize the difference even though they used different usage words, and this resulted in ineffective communication. This study emphasizes the fact that the difference in usage of words used by participants reduces the effectiveness of communication. However, if discourse participants pay attention to the differences of these usages and recognize that there are different discourses, this study suggests that meta - level learning can be possible by overcoming communication discontinuities and resolving conflicts.

Feature Vector Extraction for Solar Energy Prediction through Data Visualization and Exploratory Data Analysis (데이터 시각화 및 탐색적 데이터 분석을 통한 태양광 에너지 예측용 특징벡터 추출)

  • Jung, Wonseok;Ham, Kyung-Sun;Park, Moon-Ghu;Jeong, Young-Hwa;Seo, Jeongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.514-517
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    • 2017
  • In solar photovoltaic systems, power generation is greatly affected by the weather conditions, so it is essential to predict solar energy for stable load operation. Therefore, data on weather conditions are needed as inputs to machine learning algorithms for solar energy prediction. In this paper, we use 15 kinds of weather data such as the precipitation accumulated during the 3 hours of the surface, upward and downward longwave radiation average, upward and downward shortwave radiation average, the temperature during the past 3 hours at 2 m above from the ground and temperature from the ground surface as input data to the algorithm. We analyzed the statistical characteristics and correlations of weather data and extracted the downward and upward shortwave radiation averages as a major elements of a feature vector with high correlation of 70% or more with solar energy.

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Classical Music Review on Instagram: Accumulating Cultural Capital through Inter-Learning (클래식음악 애호가의 인스타그램 리뷰: 상호 학습을 통한 문화자본 축적)

  • Seong, Yeonju
    • Review of Culture and Economy
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    • v.21 no.2
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    • pp.111-139
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    • 2018
  • This study is about classical music lovers who write a lengthy concert review on instagram. The intention and objective of writing a review is discussed in addition to inter-communication between those reviewers. For the analysis, an interview with 8 reviewers are mainly analyzed with their reviews. As a result, it is found that some affordances of Instagram, easiness, randomness, and friendliness affects them to use Instagram more than other social media. Hence, since Instagram is image-based platform, it helps writers to keep their reviews from getting an attention by other users. Because of their sense of inferiority that they are lacking in classical music knowledge, continuous writing and reading of reviews help them accumulating some amount of cultural capital needed for understanding classical music in a proper way.

The Effects of Coding Education Using the Unplugged Robot Education System on the Perceived Useful and Easy

  • Song, JeongBeom
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.8
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    • pp.121-128
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    • 2015
  • This study aimed to investigate the effects of an unplugged robot education system capable of computerless coding education. Specifically, this study compared this education system with PicoCricket, an educational robot that can also be used with elementary students in lower grades, using assessment tools on perceived usefulness and ease. Using random sampling and randomized assignment for more objective validation, 30 participants were assigned to the unplugged robot education system group (experimental group) and 30 participants were assigned to the PicoCricket group (control group), for a total of 60 study participants. The research procedure included verification of the equivalence of the two groups by conducting a pretest after a 2-hour basic training session on algorithms and programming. The experimental and control groups learned the same content using different educational tools in accordance with software training guidelines for a total of 12 hours. Then, the difference in perceived usefulness and ease between the two groups was examined using a post-treatment test. The study results showed that scores on both dependent variables, perceived usefulness and perceived ease, were significantly higher in the experimental group than the control group. Moreover, scores on all sub-variables of the dependent variables were significantly higher in the experimental group than the control group. These results suggest that learners using the unplugged robot education system found it more useful and easier to use than learners using the existing educational robot, PicoCricket. This study's findings are significant, as according to the technology acceptance model, the perceived usefulness and ease of an educational tool are important variables that determine the acceptance of the tool (i.e., persistence of learning).

The Effects of Action Observation Combined with Modified Constraint-induced Movement Therapy on Upper-extremity Function of Subacute Stroke Patients with Moderate Impairment -A Single-blinded Randomized Controlled Trial-

  • Bang, Dae-Hyouk;Lee, Soon-Hyun
    • PNF and Movement
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    • v.18 no.1
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    • pp.23-34
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    • 2020
  • Purpose: To explore the effects of action observation combined with modified constraint-induced movement therapy on upper-extremity function and the activities of daily living in subacute stroke patients. Methods: Twenty-four subacute stroke patients were randomly assigned to the experimental group or the control group (n = 12 each). Both groups received therapy based on motor learning concepts, including repetitive and task-specific practice. The experimental group watched video clips for 10 minutes related to tasks performed during modified constraint-induced movement therapy while the control group watched videos unrelated to upper-extremity movement. These programs were performed for 40 minutes a day five times a week for four weeks. Their scores on the Fugl-Meyer assessment of upper extremities (FMA-UE), the action research arm test (ARAT), a motor activity log (amount of use [AOU] and quality of movement [QOM]), and the modified Barthel index (MBI) were recorded. Results: In both groups, all variables were significantly different between the pre-test and post-test periods (p < 0.05). The post-test variables were significantly different within each group (p < 0.05). In the experimental group, the changes between pre-test and post-test scores in the FMA-UE (14.39 ± 4.31 versus 6.31 ± 4.63), the ARAT (16.00 ± 4.73 versus 11.46 ± 3.73), MAL-AOU (1.57 ± 0.15 versus 1.18 ± 0.28), and MBI (27.54 ± 4.65 versus 18.08 ± 8.52) were significantly higher than those of the control group (p < 0.05). Conclusion: These findings suggest that action observation combined with modified constraint-induced movement therapy may be a beneficial rehabilitation option to improve upper-extremity function in subacute stroke patients with moderate impairment.