• Title/Summary/Keyword: frequency tracking

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Issue tracking and voting rate prediction for 19th Korean president election candidates (댓글 분석을 통한 19대 한국 대선 후보 이슈 파악 및 득표율 예측)

  • Seo, Dae-Ho;Kim, Ji-Ho;Kim, Chang-Ki
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.199-219
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    • 2018
  • With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

A Study on the RFID's Application Environment and Application Measure for Security (RFID의 보안업무 적용환경과 적용방안에 관한 연구)

  • Chung, Tae-Hwang
    • Korean Security Journal
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    • no.21
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    • pp.155-175
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    • 2009
  • RFID that provide automatic identification by reading a tag attached to material through radio frequency without direct touch has some specification, such as rapid identification, long distance identification and penetration, so it is being used for distribution, transportation and safety by using the frequency of 125KHz, 134KHz, 13.56MHz, 433.92MHz, 900MHz, and 2.45GHz. Also it is one of main part of Ubiquitous that means connecting to net-work any time and any place they want. RFID is expected to be new growth industry worldwide, so Korean government think it as prospective field and promote research project and exhibition business program to linked with industry effectively. RFID could be used for access control of person and vehicle according to section and for personal certify with password. RFID can provide more confident security than magnetic card, so it could be used to prevent forgery of register card, passport and the others. Active RFID could be used for protecting operation service using it's long distance date transmission by application with positioning system. And RFID's identification and tracking function can provide effective visitor management through visitor's register, personal identification, position check and can control visitor's movement in the secure area without their approval. Also RFID can make possible of the efficient management and prevention of loss of carrying equipments and others. RFID could be applied to copying machine to manager and control it's user, copying quantity and It could provide some function such as observation of copy content, access control of user. RFID tag adhered to small storage device prevent carrying out of item using the position tracking function and control carrying-in and carrying-out of material efficiently. magnetic card and smart card have been doing good job in identification and control of person, but RFID can do above functions. RFID is very useful device but we should consider the prevention of privacy during its application.

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Method Extracting Observation Data by Spatial Factor for Analysis of Selective Attention of Vision (시각의 선택적 주의집중 분석을 위한 공간요소별 주시데이터 추출방법)

  • Kim, Jong-Ha;Kim, Ju-Yeon
    • Science of Emotion and Sensibility
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    • v.18 no.4
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    • pp.3-14
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    • 2015
  • This study has extracted observation data by spatial factor for the analysis of subjects' selective attention with the objects of public space at the entrance of subway stations. The methods extracting observation data can be summarized as the following. First, the frequency analysis by lattice was prevalent for those methods, but there is a limitation to the analysis of the observation data. On the contrary, the method extracting observation data by factor applied in this study can make it clear if any sight is concentrated on any particular factors in a space. Second, the results from the extracted data corresponding to the observation area can be objectified while the method setting up the observation area by applying the radius of fovea. Third, time-sequential trace of observation results of relevant factors was possible through hourly analysis of spatial factors. The consideration of the results of "corresponding spatial scope" which is the object of this study will reveal that the more the observation time, the less the degree of attention it receives. Fourth, the frequency of observation superiority was applied for the analysis of the sections with selective attention by time scope; this revealed that men and women had intensive observation in time scope I (52.4 %) and in time scope IV (24.0 %), respectively.

A New Resource Allocation with Rate Proportionality Constraints in OFDMA Systems (OFDMA 시스템에서 비율적 전송률 분배를 위한 자원 할당)

  • Han, Seung-Youp;Oh, Eun-Sung;Han, Myeong-Su;Hong, Dae-Sik
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.45 no.1
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    • pp.59-65
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    • 2008
  • In this paper, a new adaptive resource allocation scheme is proposed in orthogonal frequency-division multiple access(OFDMA) systems with rate proportionality constraints. The problem of maximizing the overall system capacity with constraints on bit error rate, total transmission power and rate-proportionality for user requiring different classes of service is formulated. Since the optimal solution to the constrained fairness problem is extremely complex to obtain, a low-complexity suboptimal algorithm that separates subchannel allocation and power allocation is proposed. Firstly, the number of subchannels to be assigned to each user is determined based on the users' average signal-to-noise ratio and rate-proportion. Subchannels are subsequently distributed according to the modified max-min criterion. Lastly, based on the subchannel allocation, the optimal power allocation by solving the Language dual problem is proposed. Additionally, in order to reduce the computational complexity, iterative rate proportionality tracking algorithm is proposed for maximizing the capacity together with maintaining the rate proportionality constraint.

Dynamic-Response-Free SMPS Using a New High-Resolution DPWM Generator Based on Switched-Capacitor Delay Technique (Switched-Capacitor 지연 기법의 새로운 고해상도 DPWM 발생기를 이용한 Dynamic-Response-Free SMPS)

  • Lim, Ji-Hoon;Park, Young-Kyun;Wee, Jae-Kyung;Song, In-Chae
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.49 no.1
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    • pp.15-24
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    • 2012
  • In this paper, we suggest the dynamic-response-free SMPS using a new high-resolution DPWM generator based on switched-capacitor delay technique. In the proposed system, duty ratio of DPWM is controlled by voltage slope of an internal capacitor using switched-capacitor delay technique. In the proposed circuit, it is possible to track output voltage by controlling current of the internal capacitor of the DPWM generator through comparison between the feedback voltage and the reference voltage. Therefore the proposed circuit is not restricted by the dynamic-response characteristic which is a problem in the existing SMPS using the closed-loop control method. In addition, it has great advantage that ringing phenomenon due to overshoot/undershoot does not appear on output voltage. The proposed circuit can operate at switching frequencies of 1MHz~10MHz using internal operating frequency of 100 MHz. The maximum current of the core circuit is 2.7 mA and the total current of the entire circuit including output buffer is 15 mA at the switching frequency of 10 MHz. The proposed circuit has DPWM duty ratio resolution of 0.125 %. It can accommodate load current up to 1 A. The maximum ripple of output voltage is 8 mV. To verify operation of the proposed circuit, we carried out simulation with Dongbu Hitek BCD $0.35{\mu}m$ technology parameter.

A Context-Aware System for Reliable RFID-based Logistics Management (RFID 기반 물류관리의 신뢰성 향상을 위한 상황인지 시스템 개발)

  • Jin, Hee-Ju;Kim, Hoontae;Lee, Yong-Han
    • The Journal of Society for e-Business Studies
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    • v.18 no.2
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    • pp.223-240
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    • 2013
  • RFID(Radio Frequency Identification) is use of an RFID tag applied to object for the purpose of identification and tracking using radio waves. Recently, it is being actively researched and introduced in logistics and manufacturing. RFID portals in supply chains are meant to identify all the tags within a given interrogation zone. Hence the hardware and software mechanisms for RFID tag identification mostly focus on successful read of multiple tags simultaneously. Such mechanisms, however, are inefficient for determining moving direction of tags, sequence of consecutive tags, and validity of the tag reads from the viewpoint of workflow. These types of problems usually cause many difficulties in RFID portal implementation in manufacturing environment, there by having RFID-system developers waste a considerable amount of time. In this research, we designated an RFID portal system with SDO(Sequence, Direction, and Object-flow)-perception capability by using fundamental data supplied by ordinary RFID readers. Using our work, RFID system developers can save a great amount of time building RFID data-capturing applications in manufacturing environment.

Paternity Diagnosis using The Multiplex PCR with Microsatellite Markers in Dogs

  • Kim, Seung-Chang;Jang, Hong-Chul;Kim, Lee-Kyung;Lim, Da-Jeong;Lee, Seung-Hwan;Cho, Yong-Min;Kim, Tae-Hun;Seong, Hwan-Hoo;Oh, Sung-Jong;Choi, Bong-Hwan
    • Reproductive and Developmental Biology
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    • v.35 no.4
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    • pp.399-405
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    • 2011
  • The number of abandoned dogs is increasing with the worsening of the economy and the rising of feed value. It was becoming a serious social problem because of the disease transmission and destruction of natural ecosystems by abandoned dogs been wild animal. In order to solve these problems, companion dogs necessary to secure its own genetic information and to establish the systematic tracking system. Using multiplex-PCR method with 27 microsatellite marker (MS marker) divided 3 set, various alleles occurring to 6 dog breed (Labrador Retriever, German Shepherd, English Springer Spaniel, Belgian Malinois, Jindo Dog, PoongSan Dog) make use of markers to determine allele frequency and heterozygosity. MS marker FH2834 and FH2790 have only two allele and most were found in 13 alleles at FH3381 and FH3399. Average heterozygosity of MS marker is 0.534 and especially, heterozygosity represented the highest value of 0.765 at FH3381. So, it was recognized appropriate allele frequency for individual identification and paternity diagnosis in companion dogs. Using multiplex-PCR method with MS marker, various alleles occurring to dog breed make use of markers to deter mine individual identification and paternity diagnosis, traits associated biomarkers and breed-specific marker for faster, more accurate and ways to reduce the analysis cost. Based on this result, a scientific basis was established to the existing pedigree data by applying genetics additionally. Animal registration system is expected to be conducted nationwide in future. The method expects to very useful this system.

Behavioral analysis of rock bream Oplegnathus fasciatus reveals a strong attraction potential for sea urchin extracts

  • Duminda, S.K. Tilan Chamara;Kim, Yeo-Reum;Kim, Jong-Myoung
    • Fisheries and Aquatic Sciences
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    • v.24 no.1
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    • pp.32-40
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    • 2021
  • Monitoring fish movement is important to understand how physiology adapts to environmental change. To explore the applicability of a video tracking system for determining if chemical cues attract or repel aquatic animals, the movement patterns of rock bream, Oplegnathus fasciatus, were analyzed upon exposure to various materials, including extracts of sea urchin, rock worm, bait worm, krill, barley kernel, and commercial fish feed. Pellets were prepared by mixing freeze-dried tissues with a cellulose and corn flour mixture. Behavioral analysis was carried out with five fish that had been acclimated in the adaptation zone of a Y-shaped tank. Preference toward chemical cues was quantified by assessing the frequency rock bream were observed in a discrete zone around the test material located at the end of each arm and the duration each fish stayed in each zone. The analysis of fish movement upon exposure to commercial feed and barley kernel at each end, respectively, indicated a clear preference toward the feed relative to the barley kernel. Movement responses were further tested with pellets containing extracts of sea urchin, one of the species collected on a large scale, and other materials including krill and worms. A stronger preference toward sea urchin (100%) was observed based on the duration of stay in the test zone, compared to krill (90.1 ± 44.2%), bait worm (81.1 ± 39.1%), rock worm (73.7 ± 28.9%), and barley (63.9 ± 25.9%), under the conditions tested. A detailed comparison of rock bream movements toward each material revealed significant differences in frequency and duration, respectively, between pairs of test materials including krill (74 ± 29.8 and 375.6 ± 118.9) vs. rock worm (41.5 ± 18.7 and 160.2 ± 42.6), krill (86.3 ± 22.9 and 477.1 ± 84) vs. bait worm (36.2 ± 5.5 and 166.1 ± 50.7), and rock worm (45.9 ± 26.2 and 213.7 ± 100.1) vs. bait worm (34.6 ± 21.7 and 159.5 ± 98.5). Rock bream exhibited preference for the test materials in the following order: commercial fish feed > sea urchin > krill > rock worm > bait worm > barley. The results suggest a higher potency of sea urchin extract as a rock bream fishing bait compared to the other materials that are used as commercial bait.

Shear-wave elasticity imaging with axial sub-Nyquist sampling (축방향 서브 나이퀴스트 샘플링 기반의 횡탄성 영상 기법)

  • Woojin Oh;Heechul Yoon
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.5
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    • pp.403-411
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    • 2023
  • Functional ultrasound imaging, such as elasticity imaging and micro-blood flow Doppler imaging, enhances diagnostic capability by providing useful mechanical and functional information about tissues. However, the implementation of functional ultrasound imaging poses limitations such as the storage of vast amounts of data in Radio Frequency (RF) data acquisition and processing. In this paper, we propose a sub-Nyquist approach that reduces the amount of acquired axial samples for efficient shear-wave elasticity imaging. The proposed method acquires data at a sampling rate one-third lower than the conventional Nyquist sampling rate and tracks shear-wave signals through RF signals reconstructed using band-pass filtering-based interpolation. In this approach, the RF signal is assumed to have a fractional bandwidth of 67 %. To validate the approach, we reconstruct the shear-wave velocity images using shear-wave tracking data obtained by conventional and proposed approaches, and compare the group velocity, contrast-to-noise ratio, and structural similarity index measurement. We qualitatively and quantitatively demonstrate the potential of sub-Nyquist sampling-based shear-wave elasticity imaging, indicating that our approach could be practically useful in three-dimensional shear-wave elasticity imaging, where a massive amount of ultrasound data is required.

Twitter Issue Tracking System by Topic Modeling Techniques (토픽 모델링을 이용한 트위터 이슈 트래킹 시스템)

  • Bae, Jung-Hwan;Han, Nam-Gi;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.109-122
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    • 2014
  • People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.