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IEEE International Conference on Electro Information Technology

作者： Li, Li Wang, Wei Choi, Ken Park, Seongmo Chung, Moo-Kyoung Department of Electrical and Computer Engineering Illinois Institute of Technology United States IT Convergence and Components Laboratory SoC RandD Group Electronics and Telecommunications Research Institute Korea Republic of

ISBN: (纸本)9781424468751

For ultra-low-power multimedia mobile processor (MMP) design, clock-power reduction is critical because the largest portion of the total power (more than 60% in the processor designs used in this paper) is consumed in the sequential logic. Currently, for the clock-power reduction, traditional combinational clock gating scheme has been used in industry and recently, sequential clock gating method is introduced by a few advanced CAD vendors. In order to maximize the power reduction of the MMP design, we propose a novel selective sequential clock gating (SeSCG) technique in this paper. The SeSCG scheme can choose optimal sequential clock gating style selectively for ultra-low-power design based on the proposed toggle rate analysis at RT level. We have tested the proposed technique on two real industrial MMP designs using 65 nanometer technology. The experimental results show that the conventional sequential clock gating scheme even increases average 4.77% of total power while the proposed SeSCG technique decreases average 23.71% total power with reasonably very small area overhead (no more than 0.63%) when we use real industrial testbenches for the two industrial MMP designs. © 2010 IEEE.

关键词： Clocks

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Understanding postal delivery areas in the Republic of Korea using multiple unsupervised learning approaches

Understanding postal delivery areas in the Republic of Korea...

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作者： Han, Keejun Yu, Yeongwoong Na, Dong-gil Jung, Hoon Heo, Younggyo Jeong, Hyeoncheol Yun, Sunguk Kim, Jungeun Intelligent Convergence Research Laboratory Electronics and Telecommunications Research Institute Daejeon Korea Republic of Department of Computer Science and Engineering Kongju National University Cheonan Korea Republic of

Changes in household composition and the residential environment have had a considerable impact on the features of postal delivery regions in recent years, resulting in a large increase in the overall workload of domestic postal delivery services. In this paper, we provide complex analysis results for postal delivery areas using various unsupervised learning approaches. First, we extract highly influential features using several feature-engineering methods. Then, using quantitative and qualitative cluster analyses, we find the distinctive traits and semantics of postal delivery zones. Unsupervised learning approaches are useful for successfully grouping postal service zones, according to our findings. Furthermore, by comparing a postal delivery region to other areas in the same group, workload balancing was achieved. 1225-6463/$ © 2022 ETRI.

关键词： Cluster analysis

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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The design and implementation of augmented reality learning systems

The design and implementation of augmented reality learning ...

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2012 IEEE/ACIS 11th International Conference on computer and Information Science, ICIS 2012

作者： Oh, Sejin Byun, Yungcheol Convergence R and D Laboratory LG Electronics Seoul Korea Republic of Department of Computer Engineering Jeju National University Jeju-do Jeju-si Korea Republic of

ISBN: (纸本)9780769546940

In this paper, we present an augmented reality learning system that enables users to experience an interactive flower garden with the assistance of interactive agents in the augmented picture. We develop an interactive agent that generates problem-solving peer support to a user's action. We overlay virtual flower garden over a physical book and offer a collaborative environment that allows a learner to interact with the agent. To evaluate the effectiveness of the proposed system, we implement it on a mobile device and enable users to experience the collaborative task with the animated character. Through evaluation, we found that the interactive agent could be a promising technology for motivating users to engage in learning systems. © 2012 IEEE.

关键词： Learning systems

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Effective Return Rate Prediction of Blockchain Financial Products Using Machine Learning

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computers, Materials & Continua 2023年第1期74卷 2303-2316页

作者： K.Kalyani Velmurugan Subbiah Parvathy Hikmat A.M.Abdeljaber T.Satyanarayana Murthy Srijana Acharya Gyanendra Prasad Joshi Sung Won Kim PG and Research Department of Computer Science Marudupandiyar College(Affiliated to Bharathidasan UniversityTiruchirappalli)Thanjavur613403India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626126TamilnaduIndia Department of Computer Science Faculty of Information TechnologyApplied Science Private UniversityAmmanJordan Department of Information Technology Chaitanya Bharathi Institute of TechnologyHyderabadTelangana500075India Department of Convergence Science Kongju National UniversityGongju32588Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced *** successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial *** stockholders focused on the prediction of return rate and risk rate of financial ***,an automatic return rate bitcoin prediction model becomes essential for BC financial *** newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive *** study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial *** presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial ***,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification *** application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return *** experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many *** experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.

关键词： Financial products blockchain return rate prediction model machine learning parameter optimization

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3D Head Pose Estimation through Facial Features and Deep Convolutional Neural Networks

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computers, Materials & Continua 2021年第2期66卷 1757-1770页

作者： Khalil Khan Jehad Ali Kashif Ahmad Asma Gul Ghulam Sarwar Sahib Khan Qui Thanh Hoai Ta Tae-Sun Chung Muhammad Attique Department of Computer Science and Software Engineering Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur-KPKPakistan Department of Computer Engineering and Department of AI Convergence Network Ajou UniversitySuwon16499South Korea Hamad Bin Khalifa University DohaQatar Department of Statistics Shaheed Benazir Bhutto Women UniversityPeshawarPakistan Department of Software Engineering University of Azad Jammu and KashmirPakistan Department of Electronics and Telecommunications Politecnico di TorinoTorino10129Italy Institute of Research and Development Duy Tan UniversityDanang550000Vietnam Department of Computer Engineering Ajou UniversitySuwon16499Korea Department of Software Sejong UniversitySeoul05006South Korea

Face image analysis is one among several important cues in computer *** the last five decades,methods for face analysis have received immense attention due to large scale applications in various face analysis *** parsing strongly benefits various human face image analysis tasks inducing face pose *** this paper we propose a 3D head pose estimation framework developed through a prior end to end deep face parsing *** have developed an end to end face parts segmentation framework through deep convolutional neural networks(DCNNs).For training a deep face parts parsing model,we label face images for seven different classes,including eyes,brows,nose,hair,mouth,skin,and *** extract features from gray scale images by using *** train a classifier using the extracted *** use the probabilistic classification method to produce gray scale images in the form of probability maps for each dense semantic *** use a next stage of DCNNs and extract features from grayscale images created as probability maps during the segmentation *** assess the performance of our newly proposed model on four standard head pose datasets,including Pointing’04,Annotated Facial Landmarks in the Wild(AFLW),Boston University(BU),and ICT-3DHP,obtaining superior results as compared to previous results.

关键词： Face image analysis face parsing face pose estimation

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An implementation of GSG with parallel outputs targeting MIMO detector

An implementation of GSG with parallel outputs targeting MIM...

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68th Semi-Annual IEEE Vehicular Technology, VTC 2008-Fall, Conference

作者： Soo, Yun Hwang Gi, Yoon Park Hyeong, Jun Park Kyoung, Son Jhang Mobile Convergence Research Department Electronics and Telecommunications Research Institute Taejon 305-700 Korea Republic of Department of Computer Engineering Chungnam National University Taejon 305-764 Korea Republic of

ISBN: (纸本)9781424417223

Existing GSG (Gold Sequence Generator) generates only 1 bit data per clock cycle. Thus it may cause delay to the data communications. In this paper, we propose the GSG with parallel outputs for high speed data communications. Through simple matrix multiplications, we could not only derive a recursive formula in parallel form but also implement the GSG with multiple outputs. Experimental results show that though the total area and clock period of the proposed scheme are 3-13% and 21-23% larger than those of the existing scheme, our GSGs with parallel outputs improve 2, 4 and 6 times the throughput, respectively, compared with the existing GSG with single output. We also applied our GSGs to a MMSE-SIC receiver for MIMO-OFDMA systems. Therefore, we remarkably improve the throughput of the MIMO detector with the parallel processing of the data communications. ©2008 IEEE.

关键词： Orthogonal frequency division multiplexing

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A new virtualized environment for application deployment based on docker and AWS

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International Conference on Information Science and Applications, ICISA 2016

作者： Tihfon, Gemoh Maliva Kim, Jinsul Kim, Kuinam J. School of Electronics and Computer Engineering Chonnam National University Gwangju500-757 Korea Republic of Convergence Security Department Kyonggi University SuwonGyonggi-Do Korea Republic of

ISBN: (纸本)9789811005565

The setup environment and deployment of distributed applications is a human intensive and highly complex process that poses significant challenges. Nowadays many applications are developed in the cloud and existing applications are migrated to the cloud because of the promising advantages of cloud computing. The very core of cloud computing is virtualization. In this paper, we will look at application deployment with Docker. Docker is a lightweight containerization technology that has gained widespread popularity in recent years. It uses a host of the Linux kernel’s features such as namespaces and croup’s to sandbox processes into configurable virtual environments. Presenting two common serious challenging scenarios in the software development environment, we propose a multi-task PaaS cloud infrastructure using Docker and AWS services for application isolation/optimization and rapid deployment of distributed applications. © Springer Science+Business Media Singapore 2016.

关键词： Cloud computing

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Electrical stability of ZnO TFT during gate-bias stress

Electrical stability of ZnO TFT during gate-bias stress

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International Symposium of the Society-for-Information-Display (SID 2008)

作者： Kim, Tae-Hyun Kim, Sho-Yeon Jeon, Jae-Hong Choe, Hee-Hwan Lee, Kang-Woong Seo, Jong-Hyun Shin, Jae-Heon Park, Sang-Hee Ko Hwang, Chi-Sun School of Electronics Telecommunications and Computer Engineering Korea Aerospace University Goyang Gyeongki South Korea Department of Materials Science and Engineering Korea Aerospace University Goyang Gyeongki South Korea IT Convergence and Components Laboratory Electronics and Telecommunications Research Institute Yuseong Daejeon South Korea

We fabricated TFTs with ZnO thin film as an active layer. Electrical bias stress test of ZnO TFT was also carried out. The results of stress test of ZnO TFT differed from those of a-Si:H TFT Therefore, the instability, of ZnO TFT cannot be explained by conventional degradation mechanisms of a-Si:H TFT The variance of some factors in the fabrication process showed a certain trend in the results of bias stress. A possible mechanism of abnormal behavior under the gate bias stress was discussed.

关键词： Zinc oxide

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Policy-based reprogramming for wireless sensor networks

Policy-based reprogramming for wireless sensor networks

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2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops, ISORC Workshops 2010

作者： Lee, Sang Hoon Choi, Lynn Nah, Yunmook Hong, Seungki Jun, Jong-Arm School of Electrical Engineering Korea University Seoul Korea Republic of Department of Electronics and Computer Engineering Dankook University Yongin Korea Republic of Research Laboratory IT Convergence Technology ETRI Daejeon Korea Republic of

ISBN: (纸本)9780769540382

Program codes running on the sensor nodes need to be updated from time to time to fix bugs, tune the parameters, insert new functions, or delete useless codes. In this paper, we propose a policy-based reprogramming framework that can optimize the reprogramming process based on the execution characteristics of modules that constitute the WSN applications. To accomplish this we model the characteristics of a module as a tuple of the following four criteria;region, residence, synchronization and real-time properties of the module. According to the class of a module and the type of a reprogramming operation, we adaptively use 3 different reprogramming techniques;efficient code dissemination using connected dominating set, selective code dissemination, and code acquisition. Experimentation results confirm that this policy-based reprogramming can achieve substantial improvement in both the energy consumption and the reprogramming latency compared to existing solutions for various reprogramming scenarios. © 2010 IEEE.

关键词： Energy utilization

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