• Title/Summary/Keyword: software framework

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Fast Computation of DWT and JPEG2000 using GPU (GPU를 이용한 DWT 및 JPEG2000의 고속 연산)

  • Lee, Man-Hee;Park, In-Kyu;Won, Seok-Jin;Cho, Sung-Dae
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.6
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    • pp.9-15
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    • 2007
  • In this paper, we propose an efficient method for Processing DWT (Discrete Wavelet Transform) on GPU (Graphics Processing Unit). Since the DWT and EBCOT (embedded block coding with optimized truncation) are the most complicated submodules in JPEG2000, we design a high-performance processing framework for performing DWT using the fragment shader of GPU based on the render-to-texture (RTT) architecture. Experimental results show that the performance increases significantly, in which DWT running on modern GPU is more than 10 times faster than on modern CPU. Furthermore, by replacing the DWT part of Jasper which is the JPEG2000 reference software, the overall processing is 2$\sim$16 times faster than the original JasPer. The GPU-driven render-to-texture architecture proposed in this paper can be used in the general image and computer vision processing for high-speed processing.

Constructing a Support Vector Machine for Localization on a Low-End Cluster Sensor Network (로우엔드 클러스터 센서 네트워크에서 위치 측정을 위한 지지 벡터 머신)

  • Moon, Sangook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.12
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    • pp.2885-2890
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    • 2014
  • Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

Optimizing Boot Stage of Linux for Low-power ARM Embedded Devices (리눅스기반 저전력 ARM 임베디드 장비의 부팅과정 최적화)

  • Kim, Jongseok;Yang, Jinyoung;Kim, Daeyoung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.137-140
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    • 2013
  • Conventionally embedded devices used simple operating system (OS); however, the number of embedded devices using Linux as OS is increasing to keep up with hardware's performance improvement and customer's various needs. While embedded devices using Linux can take advantage of expandability, generality, portability, Linux's flexibility nature may cause undesirable overheads because of its increased complexity. One such overhead makes boot stage optimization essential in most embedded systems, where many features are redundant and possible to be removed or reconfigured. This paper applies well-known software optimization technique for Linux's boot stage to an CLM9722 DTK, measures the results, and studies about limitation of such techniques from hardware dependancy on the standard framework of Linux. The booting time from power-on until completion were decreased by 33% approximately.

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Design and Implementation of Oracle Web Courseware for Problem Solving Learning (문제 해결 학습을 위한 오라클 웹 코스웨어 설계 및 구현)

  • Cho, Do-Eun;Lee, Jie-Young
    • The Journal of Information Technology
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    • v.5 no.2
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    • pp.95-106
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    • 2002
  • This study attempts to construct and manage the distance learning system by focusing on education institutins. However, they lack not only web-based courseware for information literacy but also the contents for the management technology. This study tried to design and implement the web-based courseware by using OCP(Oracle Certified Profession) based on the initial Oracle in distance learning. Learners' individual variations were considered based on problem solving learning. Also, the practical contents that could be applied in the educational field were selected. The learning type web-based courseware, using the technology of ASP, DHTML, JAVAscript, VBA, was designed and implemented into the framework that could be updated easily. The result of the study shows: first of all, this courseware induced a greater understanding of the Oracle language and the student's interests. Secondly, the student's had more control over the process of individual learning and achieved the goal more effectively through immediate feedback, finally, the students could learn wherever they have on-line connections to the web server.

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Affine Invariant Local Descriptors for Face Recognition (얼굴인식을 위한 어파인 불변 지역 서술자)

  • Gao, Yongbin;Lee, Hyo Jong
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.9
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    • pp.375-380
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    • 2014
  • Under controlled environment, such as fixed viewpoints or consistent illumination, the performance of face recognition is usually high enough to be acceptable nowadays. Face recognition is, however, a still challenging task in real world. SIFT(Scale Invariant Feature Transformation) algorithm is scale and rotation invariant, which is powerful only in the case of small viewpoint changes. However, it often fails when viewpoint of faces changes in wide range. In this paper, we use Affine SIFT (Scale Invariant Feature Transformation; ASIFT) to detect affine invariant local descriptors for face recognition under wide viewpoint changes. The ASIFT is an extension of SIFT algorithm to solve this weakness. In our scheme, ASIFT is applied only to gallery face, while SIFT algorithm is applied to probe face. ASIFT generates a series of different viewpoints using affine transformation. Therefore, the ASIFT allows viewpoint differences between gallery face and probe face. Experiment results showed our framework achieved higher recognition accuracy than the original SIFT algorithm on FERET database.

A Conceptual Framework to Study the Effectiveness of Interface Management in Construction Projects

  • KEERTHANAA, K.;SHANMUGAPRIYA, S.
    • Journal of Construction Engineering and Project Management
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    • v.9 no.3
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    • pp.1-21
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    • 2019
  • The management of mega construction projects which incorporate a large number of stakeholders, technologies, data, work culture etc., is cumbersome. The experts in the construction arena advocate that interface management serves as a precise tool in resolving these conflict points due to the intricate nature of the construction projects. Interface management is a current trending management practice in the construction industry which is also a beneficiary to mega/fast track projects in enhancing the project performance. The main objective of this study is to validate a model for assessing the relationships among interface management, IT applications, project performance & project benefits. The mediating effect of interface management in relationship between project performance & interfacial factors was also investigated. The research model was validated using PLS-SEM (Partial Least Square-Structural Equation Modelling) approach. Data were collected from clients, contractors, consultants in large scale projects through questionnaire survey and smart-PLS software was used to analyse the conceptual model. The research model comprises eleven hypothesis and the significance of these hypothesis were tested using T- statistics values. The research implies that people/participants factor is greatly influenced by interface management with the path coefficient of 0.608 and also enhancement of project's schedule performance due to the interface management is strongly appealing (Path coefficient = 0.711). The results also reveal IT application is significantly associated with interface management practice (Path coefficient =0.723) and also the effect of IT application on project performance (schedule, cost, quality & safety) is successfully mediated through interface management practice. The practical application of this validated model was done through case study. The case study aims at measuring the impact of interface management on interfacial factors and role of interface management in improving the project performance in the construction organisations.

An optimization framework to tackle challenging cargo accommodation tasks in space engineering

  • Fasano, Giorgio;Gastaldi, Cristina;Piras, Annamaria;Saia, Dario
    • Advances in aircraft and spacecraft science
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    • v.1 no.2
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    • pp.197-218
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    • 2014
  • Quite a demanding task frequently arises in space engineering, when dealing with the cargo accommodation of modules and vehicles. The objective of this effort usually aims at maximizing the loaded cargo, or, at least, at meeting the logistic requirements posed by the space agencies. Complex accommodation rules are supposed to be taken into account, in compliance with strict balancing conditions and very tight operational restrictions. The context of the International Space Station (ISS) has paved the way for a relevant research and development activity, providing the company with a remarkable expertise in the field. CAST (Cargo Accommodation Support Tool) is a dedicated in-house software package (funded by the European Space Agency, ESA, and achieved by Thales Alenia Space), to carry out the whole loading of the Automated Transfer Vehicle (ATV). An ad hoc version, tailored to the Columbus (ISS attached laboratory) on-board stowage issue, has been further implemented and is to be used from now on. This article surveys the overall approach followed, highlighting the advantages of the methodology put forward, both in terms of solution quality and time saving, through an overview of the outcomes obtained to date. Insights on possible extensions to further space applications, especially in the perspective of the paramount challenges of the near future, are, in addition, presented.

The development of a ship's network monitoring system using SNMP based on standard IEC 61162-460

  • Wu, Zu-Xin;Rind, Sobia;Yu, Yung-Ho;Cho, Seok-Je
    • Journal of Advanced Marine Engineering and Technology
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    • v.40 no.10
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    • pp.906-915
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    • 2016
  • In this study, a network monitoring system, including a secure 460-Network and a 460-Gateway, is designed and developed according with the requirements of the IEC (International Electro-Technical Commission) 61162-460 network standard for the safety and security of networks on board ships. At present, internal or external unauthorized access to or malicious attack on a ship's on board systems are possible threats to the safe operation of a ship's network. To secure the ship's network, a 460-Network was designed and implemented by using a 460-Switch, 460-Nodes, and a 460-Gateway that contains firewalls and a DMZ (Demilitarized Zone) with various application servers. In addition, a 460-firewall was used to block all traffic from unauthorized networks. 460-NMS (Network Monitoring System) is a network-monitoring software application that was developed by using an simple network management protocol (SNMP) SharpNet library with the .Net 4.5 framework and a backhand SQLite database management system, which is used to manage network information. 460-NMS receives network information from a 460-Switch by utilizing SNMP, SNMP Trap, and Syslog. 460-NMS monitors the 460-Network load, traffic flow, current network status, network failure, and unknown devices connected to the network. It notifies the network administrator via alarms, notifications, or warnings in case any network problem occurs. Once developed, 460-NMS was tested both in a laboratory environment and for a real ship network that had been installed by the manufacturer and was confirmed to comply with the IEC 61162-460 requirements. Network safety and security issues onboard ships could be solved by designing a secure 460-Network along with a 460-Gateway and by constantly monitoring the 460-Network according to the requirements of the IEC 61162-460 network standard.

A study on systematic review of unplugged activity (언플러그드 활동의 체계적 문헌고찰에 관한 연구)

  • Kim, Jeongrang
    • Journal of The Korean Association of Information Education
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    • v.22 no.1
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    • pp.103-111
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    • 2018
  • In order to examine the educational effects and future directions of unplugged activities, we conducted a systematic review of Korean journals and theses from 2007 to 2016. Three kinds of database were used for systematic review: RISS, KISS, and E-article, and were performed searches using options such as 'unplugged' and 'play-centered'. Based on the protocol selected in the framework of the systematic review, 37 articles were selected analyzed in terms of research status, research subjects, research methods, research hubs, study mechanisms, educational methods, and research effects. Unplugged activities were the most popular among elementary school students. Educational effects were found to have significant effects on academic achievement, problem solving ability, and logical thinking ability. In the affirmative domain, there was a significant effect on interest, curiosity, and motivation. Based on the results of the analysis, the characteristics and implications of Unplugged activities and present the direction of future education were discussed.

ECG-based Biometric Authentication Using Random Forest (랜덤 포레스트를 이용한 심전도 기반 생체 인증)

  • Kim, JeongKyun;Lee, Kang Bok;Hong, Sang Gi
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.6
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    • pp.100-105
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    • 2017
  • This work presents an ECG biometric recognition system for the purpose of biometric authentication. ECG biometric approaches are divided into two major categories, fiducial-based and non-fiducial-based methods. This paper proposes a new non-fiducial framework using discrete cosine transform and a Random Forest classifier. When using DCT, most of the signal information tends to be concentrated in a few low-frequency components. In order to apply feature vector of Random Forest, DCT feature vectors of ECG heartbeats are constructed by using the first 40 DCT coefficients. RF is based on the computation of a large number of decision trees. It is relatively fast, robust and inherently suitable for multi-class problems. Furthermore, it trade-off threshold between admission and rejection of ID inside RF classifier. As a result, proposed method offers 99.9% recognition rates when tested on MIT-BIH NSRDB.