• Title/Summary/Keyword: Media decision

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A Semi-Markov Decision Process (SMDP) for Active State Control of A Heterogeneous Network

  • Yang, Janghoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.7
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    • pp.3171-3191
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    • 2016
  • Due to growing demand on wireless data traffic, a large number of different types of base stations (BSs) have been installed. However, space-time dependent wireless data traffic densities can result in a significant number of idle BSs, which implies the waste of power resources. To deal with this problem, we propose an active state control algorithm based on semi-Markov decision process (SMDP) for a heterogeneous network. A MDP in discrete time domain is formulated from continuous domain with some approximation. Suboptimal on-line learning algorithm with a random policy is proposed to solve the problem. We explicitly include coverage constraint so that active cells can provide the same signal to noise ratio (SNR) coverage with a targeted outage rate. Simulation results verify that the proposed algorithm properly controls the active state depending on traffic densities without increasing the number of handovers excessively while providing average user perceived rate (UPR) in a more power efficient way than a conventional algorithm.

Anomaly Sewing Pattern Detection for AIoT System using Deep Learning and Decision Tree

  • Nguyen Quoc Toan;Seongwon Cho
    • Smart Media Journal
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    • v.13 no.2
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    • pp.85-94
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    • 2024
  • Artificial Intelligence of Things (AIoT), which combines AI and the Internet of Things (IoT), has recently gained popularity. Deep neural networks (DNNs) have achieved great success in many applications. Deploying complex AI models on embedded boards, nevertheless, may be challenging due to computational limitations or intelligent model complexity. This paper focuses on an AIoT-based system for smart sewing automation using edge devices. Our technique included developing a detection model and a decision tree for a sufficient testing scenario. YOLOv5 set the stage for our defective sewing stitches detection model, to detect anomalies and classify the sewing patterns. According to the experimental testing, the proposed approach achieved a perfect score with accuracy and F1score of 1.0, False Positive Rate (FPR), False Negative Rate (FNR) of 0, and a speed of 0.07 seconds with file size 2.43MB.

Multi-Cattle Tracking Algorithm with Enhanced Trajectory Estimation in Precision Livestock Farms

  • Shujie Han;Alvaro Fuentes;Sook Yoon;Jongbin Park;Dong Sun Park
    • Smart Media Journal
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    • v.13 no.2
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    • pp.23-31
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    • 2024
  • In precision cattle farm, reliably tracking the identity of each cattle is necessary. Effective tracking of cattle within farm environments presents a unique challenge, particularly with the need to minimize the occurrence of excessive tracking trajectories. To address this, we introduce a trajectory playback decision tree algorithm that reevaluates and cleans tracking results based on spatio-temporal relationships among trajectories. This approach considers trajectory as metadata, resulting in more realistic and accurate tracking outcomes. This algorithm showcases its robustness and capability through extensive comparisons with popular tracking models, consistently demonstrating the promotion of performance across various evaluation metrics that is HOTA, AssA, and IDF1 achieve 68.81%, 79.31%, and 84.81%.

Insights Discovery through Hidden Sentiment in Big Data: Evidence from Saudi Arabia's Financial Sector

  • PARK, Young-Eun;JAVED, Yasir
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.6
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    • pp.457-464
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    • 2020
  • This study aims to recognize customers' real sentiment and then discover the data-driven insights for strategic decision-making in the financial sector of Saudi Arabia. The data was collected from the social media (Facebook and Twitter) from start till October 2018 in financial companies (NCB, Al Rajhi, and Bupa) selected in the Kingdom of Saudi Arabia according to criteria. Then, it was analyzed using a sentiment analysis, one of data mining techniques. All three companies have similar likes and followers as they serve customers as B2B and B2C companies. In addition, for Al Rajhi no negative sentiment was detected in English posts, while it can be seen that Internet penetration of both banks are higher than BUPA, rarely mentioned in few hours. This study helps to predict the overall popularity as well as the perception or real mood of people by identifying the positive and negative feelings or emotions behind customers' social media posts or messages. This research presents meaningful insights in data-driven approaches using a specific data mining technique as a tool for corporate decision-making and forecasting. Understanding what the key issues are from customers' perspective, it becomes possible to develop a better data-based global strategies to create a sustainable competitive advantage.

Initial Buffering-Time Decision Scheme for Progressive Multimedia Streaming Service (프로그레시브 멀티미디어 스트리밍 서비스를 위한 초기 버퍼링 시간 결정 기법)

  • Seo, Kwang-Deok;Jung, Soon-Heung
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.2
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    • pp.206-210
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    • 2008
  • The most noticeable aspect of progressive streaming is the media playback during its download through TCP to avoid a lengthy wait for a content to finish downloading. By employing TCP, it is usually possible to detect lost packets by using the checksum and sequence numbering functions of TCP Thereafter, we can recover the lost packets by the retransmission function of TCP. However, there must remain enough amount of media data in the recipient buffer in order to guarantee seamless media playback even during retransmission. In this paper, we propose an efficient algorithm for determining the initial buffering time before start of playback to guarantee seamless playback during retransmission considering the probability of client buffer under-flow. The effectiveness of the proposed algorithm will be proved through extensive simulation results.

Depth-map coding using the block-based decision of the bitplane to be encoded (블록기반 부호화할 비트평면 결정을 이용한 깊이정보 맵 부호화)

  • Kim, Kyung-Yong;Park, Gwang-Hoon
    • Journal of Broadcast Engineering
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    • v.15 no.2
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    • pp.232-235
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    • 2010
  • This paper proposes an efficient depth-map coding method. The adaptive block-based depth-map coding method decides the number of bit planes to be encoded according to the quantization parameters to obtain the desired bit rates. So, the depth-map coding using the block-based decision of the bit-plane to be encoded proposes to free from the constraint of the quantization parameters. Simulation results show that the proposed method, in comparison with the adaptive block-based depth-map coding method, improves the average BD-rate savings by 3.5% and the average BD-PSNR gains by 0.25dB.

An Accurate Estimation of Channel Loss Threshold Set for Optimal FEC Code Rate Decision (최적의 FEC 부호율 결정을 위한 정확한 채널손실 한계집합 추정기법)

  • Jung, Tae-Jun;Jeong, Yo-Won;Seo, Kwang-Deok
    • Journal of Broadcast Engineering
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    • v.19 no.2
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    • pp.268-271
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    • 2014
  • Conventional forward error correction (FEC) code rate decision schemes using analytical source coding distortion model and channel-induced distortion model are usually complex, and require the typical process of model parameter training which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate joint source-channel distortion model to estimate channel loss threshold set for optimal FEC code rate decision.

HEVC Fast Intra Mode Decision based on Most Probable Mode and Rough Mode Decision Cost (Most Probable Mode 와 Rough Mode Decision 비용을 함께 고려하는 HEVC 고속 화면내 부호화 모드 결정 방법)

  • Gwon, Daehyeok;Han, Heeji;Kim, Minseop;Choi, Haechul
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2015.11a
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    • pp.141-142
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    • 2015
  • 본 논문에서는 HEVC(High Efficiency Video Coding)을 위한 고속 부호화 알고리즘을 제안한다. 제안 방법은 HEVC 의 화면내 부호화 과정에서 주변 부호화 모드 정보인 MPM(Most Probable Mode)과 RMD(Rough Mode Decision) 과정의 결과로 얻어지는 후보 모드들의 상관관계를 이용하여 높은 계산 복잡도를 가지는 RDO(Rate-Distortion Optimization) 과정이 고려하는 후보의 개수를 줄여 전체 부호화기의 부호화 복잡도를 낮춘다. 실험 결과에서는 제안 방법이 약 0.29% BD-rate 의 부호화 손실만으로 20.43%의 부호화 복잡도를 감소시켰음을 보인다.

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Frequency Adaptive Hard-Decision Quantization for Video Coding (영상 부호화를 위한 주파수 적응형 경판정 양자화)

  • Xu, Motong;Jeon, Byeungwoo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.194-195
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    • 2019
  • In this paper, we propose a frequency location adaptive hard-decision quantization (HDQ) scheme for video coding. A threshold for zero quantized level is adaptively applied to unquantized transform coefficients based on its frequency location in the transform domain. The proposed method achieves an average of 1.13%, 1.57%, and 1.53% of bit-rate reduction in BDBR sense compared to the conventional HDQ scheme respectively in Y, Cb, and Cr under the all intra encoding configuration.

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MONJUnoCHIE SYSTEM : VIDEOCONFERENCE SYSTEM WITH EYE CONTACT FOR DECISION MAKING

  • Terumasa Aoki;Kustarto Widoyo;Nobuki Sakamoto
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.06a
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    • pp.177-182
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    • 1999
  • With the recent evolutionary progress in network and terminal technologies, current videoconference systems are in the level of practical use. The existing systems, however, would not be fully useful for decision making process since eyes of users can not always be in contact that makes it difficult to read the expression of participants. In this paper, we discuss the principle and the impact of“MONJUnoCHIE System”a videoconference system with eye contact using a special display device called“Glass Vision”.