• Title/Summary/Keyword: Video analysis system

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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.

Hate Speech Detection Using Modified Principal Component Analysis and Enhanced Convolution Neural Network on Twitter Dataset

  • Majed, Alowaidi
    • International Journal of Computer Science & Network Security
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    • v.23 no.1
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    • pp.112-119
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    • 2023
  • Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

Development of an Offline Based Internal Organ Motion Verification System during Treatment Using Sequential Cine EPID Images (연속촬영 전자조사 문 영상을 이용한 오프라인 기반 치료 중 내부 장기 움직임 확인 시스템의 개발)

  • Ju, Sang-Gyu;Hong, Chae-Seon;Huh, Woong;Kim, Min-Kyu;Han, Young-Yih;Shin, Eun-Hyuk;Shin, Jung-Suk;Kim, Jing-Sung;Park, Hee-Chul;Ahn, Sung-Hwan;Lim, Do-Hoon;Choi, Doo-Ho
    • Progress in Medical Physics
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    • v.23 no.2
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    • pp.91-98
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    • 2012
  • Verification of internal organ motion during treatment and its feedback is essential to accurate dose delivery to the moving target. We developed an offline based internal organ motion verification system (IMVS) using cine EPID images and evaluated its accuracy and availability through phantom study. For verification of organ motion using live cine EPID images, a pattern matching algorithm using an internal surrogate, which is very distinguishable and represents organ motion in the treatment field, like diaphragm, was employed in the self-developed analysis software. For the system performance test, we developed a linear motion phantom, which consists of a human body shaped phantom with a fake tumor in the lung, linear motion cart, and control software. The phantom was operated with a motion of 2 cm at 4 sec per cycle and cine EPID images were obtained at a rate of 3.3 and 6.6 frames per sec (2 MU/frame) with $1,024{\times}768$ pixel counts in a linear accelerator (10 MVX). Organ motion of the target was tracked using self-developed analysis software. Results were compared with planned data of the motion phantom and data from the video image based tracking system (RPM, Varian, USA) using an external surrogate in order to evaluate its accuracy. For quantitative analysis, we analyzed correlation between two data sets in terms of average cycle (peak to peak), amplitude, and pattern (RMS, root mean square) of motion. Averages for the cycle of motion from IMVS and RPM system were $3.98{\pm}0.11$ (IMVS 3.3 fps), $4.005{\pm}0.001$ (IMVS 6.6 fps), and $3.95{\pm}0.02$ (RPM), respectively, and showed good agreement on real value (4 sec/cycle). Average of the amplitude of motion tracked by our system showed $1.85{\pm}0.02$ cm (3.3 fps) and $1.94{\pm}0.02$ cm (6.6 fps) as showed a slightly different value, 0.15 (7.5% error) and 0.06 (3% error) cm, respectively, compared with the actual value (2 cm), due to time resolution for image acquisition. In analysis of pattern of motion, the value of the RMS from the cine EPID image in 3.3 fps (0.1044) grew slightly compared with data from 6.6 fps (0.0480). The organ motion verification system using sequential cine EPID images with an internal surrogate showed good representation of its motion within 3% error in a preliminary phantom study. The system can be implemented for clinical purposes, which include organ motion verification during treatment, compared with 4D treatment planning data, and its feedback for accurate dose delivery to the moving target.

Learning Material Bookmarking Service based on Collective Intelligence (집단지성 기반 학습자료 북마킹 서비스 시스템)

  • Jang, Jincheul;Jung, Sukhwan;Lee, Seulki;Jung, Chihoon;Yoon, Wan Chul;Yi, Mun Yong
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.179-192
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    • 2014
  • Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

A Study on Relationship between Physical Elements and Tennis/Golf Elbow

  • Choi, Jungmin;Park, Jungwoo;Kim, Hyunseung
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.3
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    • pp.183-196
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    • 2017
  • Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.

Enterprise Human Resource Management using Hybrid Recognition Technique (하이브리드 인식 기술을 이용한 전사적 인적자원관리)

  • Han, Jung-Soo;Lee, Jeong-Heon;Kim, Gui-Jung
    • Journal of Digital Convergence
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    • v.10 no.10
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    • pp.333-338
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    • 2012
  • Human resource management is bringing the various changes with the IT technology. In particular, if HRM is non-scientific method such as group management, physical plant, working hours constraints, personal contacts, etc, the current enterprise human resources management(e-HRM) appeared in the individual dimension management, virtual workspace (for example: smart work center, home work, etc.), working time flexibility and elasticity, computer-based statistical data and the scientific method of analysis and management has been a big difference in the sense. Therefore, depending on changes in the environment, companies have introduced a variety of techniques as RFID card, fingerprint time & attendance systems in order to build more efficient and strategic human resource management system. In this paper, time and attendance, access control management system was developed using multi camera for 2D and 3D face recognition technology-based for efficient enterprise human resource management. We had an issue with existing 2D-style face-recognition technology for lighting and the attitude, and got more than 90% recognition rate against the poor readability. In addition, 3D face recognition has computational complexities, so we could improve hybrid video recognition and the speed using 3D and 2D in parallel.

On-Road Car Detection System Using VD-GMM 2.0 (차량검출 GMM 2.0을 적용한 도로 위의 차량 검출 시스템 구축)

  • Lee, Okmin;Won, Insu;Lee, Sangmin;Kwon, Jangwoo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.11
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    • pp.2291-2297
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    • 2015
  • This paper presents a vehicle detection system using the video as a input image what has moving of vehicles.. Input image has constraints. it has to get fixed view and downward view obliquely from top of the road. Road detection is required to use only the road area in the input image. In introduction, we suggest the experiment result and the critical point of motion history image extraction method, SIFT(Scale_Invariant Feature Transform) algorithm and histogram analysis to detect vehicles. To solve these problem, we propose using applied Gaussian Mixture Model(GMM) that is the Vehicle Detection GMM(VDGMM). In addition, we optimize VDGMM to detect vehicles more and named VDGMM 2.0. In result of experiment, each precision, recall and F1 rate is 9%, 53%, 15% for GMM without road detection and 85%, 77%, 80% for VDGMM2.0 with road detection.

A Study on the Imporvement of Wireless Internet Service Tariff Scheme. (무선인터넷 데이터 서비스 과금 체계 개선 연구)

  • Min, Gyeong-Ju;Kim, Jeong-Ho;Park, Jin-Yang
    • Journal of the Korea Computer Industry Society
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    • v.5 no.9
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    • pp.1101-1110
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    • 2004
  • In the first quarter of 2004, there were about 1 billion 348 million mobile phone users worldwide with a penetration rate of only 29%. Korea ranks among the highest in the use of mobile communication, having over 36 million mobile phone subscribers with a mobile phone penetration rate of 75% as of May 2004. Since the introduction of wireless Internet service in May 1999, the number of subscribers rose to 34.5 million with 95.3% of the total mobile phone subscribers using wireless Internet services in May 2004, largely due to continued investments by telecommunication service providers, improvement of mobile handsets (color and digital camera phones) and implementation of policies on mobile number portability. In the Korean wireless Internet market, there are many user complaints since the service providers are competing with each other through TV commercial sales and phone discounts rather than improving their call quality, services and billing systems. therefore there is a growing need to improve the billing systems through means such as the implementation of reasonable payment plans according to consumer use, development of a wireless Internet billing system that can predict the number of users and establishment of pricing standards for controlled data (head, tail, etc...) as well as menu information by testing the texts. multimedia, video and other types of content provided by the three major mobile communication companies. The purpose of this study is to promote wireless Internet services and protect user rights by proposing a reasonable way to improve the billing systems for wireless Internet services after conducting a comparative analysis of file size and billing data of each of the service providers through a verification test on a packet billing system for wireless Internet services.

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Home Network Observation System Using Activate Pattern Analysis of User and Multimedia Streaming (사용자의 행동 패턴 분석과 멀티미디어 스트리밍 기술을 이용한 홈 네트워크 감시 시스템)

  • Oh Dong-Yeol;Oh Hae-Seok;Sung Kyung-Sang
    • Journal of Korea Multimedia Society
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    • v.8 no.9
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    • pp.1258-1268
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    • 2005
  • While the concept of Home Network is laying by and its interests are increasing by means of digitalizing of the information communication infrastructure, many efforts are in progress toward convenient lives. Moreover, as information household appliances which have a junction of connecting to the network are appearing over the past a few years, the demands against intellectual Home Services are increasing. In this paper, by being based upon Multimedia which is an essential factor for developing of various application services on ubiquitous computing environments, we suggest a simplified application model that could apply the information to the automated processing system after studying user's behavior patterns using authentication and access control for identity certification of users. In addition, we compared captured video images in the fixed range by pixel unit through some time and checked disorder of them. And that made safe of user certification as adopting self-developed certification method which was used 'Hash' algorism through salt function of 12 byte. In order to show the usefulness of this proposed model, we did some testing by emulator for control of information after construction for Intellectual Multimedia Server, which ubiquitous network is available on as a scheme so as to check out developed applications. According to experimental results, it is very reasonable to believe that we could extend various multimedia applications in our daily lives.

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An Efficient Broadcasting Channel Assignment Scheme for Mobile VOD Services (모바일 VOD 서비스를 위한 브로드캐스팅 채널할당 기법)

  • Choi, Young
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.685-691
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    • 2008
  • Recently with the rapid evolution of the mobile computing and communication technologies, mobile VOD service becomes increasingly important for wireless mobile users. The VOD service is being widely used in various areas of application, such as education, entertainment and business, because it provides users convenience in easily having access to video information at any time in any places. However, in reality, the mobile system has many difficulties in providing the smooth VOD service owing to frequent transfers and cutoffs of clients. The importance of a technique to transmit broadcasting is being stressed as a method for providing stabler mobile VOD service to a large number of clients. This paper is aimed at showing how to reduce demands for server bandwidth and delay of earlier service through performance analysis by suggesting an effective VOD broadcasting transmission technique through channel division in the mobile atmosphere. Many researches have been made about regular broadcasting techniques in particular. This study divides the methods used for assigning channels which have been decided by the size of segments into a group of regular channels and assistant channels using wireless gap-fillers to provide effective VOD services to a large number of clients at the mobile environment using small bandwidth resources. The regular channels transfer regular streams, while assistant channels repeatedly transfer the first segment to reduce early service delay time to receive regular streams. In this way, the study suggests a technique to reduce server bandwidth demand and early service delay time. Through the proposed technique, the server bandwidth demand could be reduced by more than 30 percent and the study continuously shows reduced early service delay time through conducting performance analysis.

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