• Title/Summary/Keyword: Optimal Broadcasting

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Path Algorithm for Maximum Tax-Relief in Maximum Profit Tax Problem of Multinational Corporation (다국적기업 최대이익 세금트리 문제의 최대 세금경감 경로 알고리즘)

  • Sang-Un Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.4
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    • pp.157-164
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    • 2023
  • This paper suggests O(n2) polynomial time heuristic algorithm for corporate tax structure optimization problem that has been classified as NP-complete problem. The proposed algorithm constructs tax tree levels that the target holding company is located at root node of Level 1, and the tax code categories(Te) 1,4,3,2 are located in each level 2,3,4,5 sequentially. To find the maximum tax-relief path from source(S) to target(T), firstly we connect the minimum witholding tax rate minrw(u, v) arc of node u point of view for transfer the profit from u to v node. As a result we construct the spanning tree from all of the source nodes to a target node, and find the initial feasible solution. Nextly, we find the alternate path with minimum foreign tax rate minrfi(u, v) of v point of view. Finally we choose the minimum tax-relief path from of this two paths. The proposed heuristic algorithm performs better optimal results than linear programming and Tabu search method that is a kind of metaheuristic method.

Effects of Spatio-temporal Features of Dynamic Hand Gestures on Learning Accuracy in 3D-CNN (3D-CNN에서 동적 손 제스처의 시공간적 특징이 학습 정확성에 미치는 영향)

  • Yeongjee Chung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.3
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    • pp.145-151
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    • 2023
  • 3D-CNN is one of the deep learning techniques for learning time series data. Such three-dimensional learning can generate many parameters, so that high-performance machine learning is required or can have a large impact on the learning rate. When learning dynamic hand-gestures in spatiotemporal domain, it is necessary for the improvement of the efficiency of dynamic hand-gesture learning with 3D-CNN to find the optimal conditions of input video data by analyzing the learning accuracy according to the spatiotemporal change of input video data without structural change of the 3D-CNN model. First, the time ratio between dynamic hand-gesture actions is adjusted by setting the learning interval of image frames in the dynamic hand-gesture video data. Second, through 2D cross-correlation analysis between classes, similarity between image frames of input video data is measured and normalized to obtain an average value between frames and analyze learning accuracy. Based on this analysis, this work proposed two methods to effectively select input video data for 3D-CNN deep learning of dynamic hand-gestures. Experimental results showed that the learning interval of image data frames and the similarity of image frames between classes can affect the accuracy of the learning model.

Optimization Algorithm for k-opt Swap of Generalized Assignment Problem (일반화된 배정 문제의 k-opt 교환 최적화 알고리즘)

  • Sang-Un Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.5
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    • pp.151-158
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    • 2023
  • The researchers entirely focused on meta-heuristic method for generalized assignment problem(GAP) that is known as NP-hard problem because of the optimal solution within polynomial time algorithm is unknown yet. On the other hand, this paper proposes a heuristic greedy algorithm with rules for finding solutions. Firstly, this paper reduces the weight matrix of original data to wij ≤ bi/l in order to n jobs(items) pack m machines(bins) with l = n/m. The maximum profit of each job was assigned to the machine for the reduced data. Secondly, the allocation was adjusted so that the sum of the weights assigned to each machine did not exceed the machine capacity. Finally, the k-opt swap optimization was performed to maximize the profit. The proposed algorithm is applied to 50 benchmarking data, and the best known solution for about 1/3 data is to solve the problem. The remaining 2/3 data showed comparable results to metaheuristic techniques. Therefore, the proposed algorithm shows the possibility that rules for finding solutions in polynomial time exist for GAP. Experiments demonstrate that it can be a P-problem from an NP-hard.

Load Modeling based on System Identification with Kalman Filtering of Electrical Energy Consumption of Residential Air-Conditioning

  • Patcharaprakiti, Nopporn;Tripak, Kasem;Saelao, Jeerawan
    • International journal of advanced smart convergence
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    • v.4 no.1
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    • pp.45-53
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    • 2015
  • This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.

A New Key Management Mechanism and Performance Improvement for Conditional Access System (제한수신시스템을 위한 키 관리 메카니즘과 성능향상 방안)

  • 조현숙;이상호
    • The KIPS Transactions:PartC
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    • v.8C no.1
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    • pp.75-87
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    • 2001
  • The Conditional Access System is the complete system for ensuring that broadcasting services are only accessible to those who are entitled to receive them. Four major parts to this system are scrambling, descrambling, authentication and encryption. For the proper operation, which means hard-to- break and uninterrupted service, secure key management and efficient delivery mechanism are very important design factors to this system. Performance analysis is another important factor to this system that is used in massive subscriber environment. In this thesis, one of the secure and efficient key management mechanisms is proposed. For the secrecy of this mechanism, hierarchical stacking of keys and key generation matrix are proposed. For the proof of efficient delivery of those keys, simulation results and performance analysis. which is based on queuing analysis, are presented. Lastly, optimal key generation and delivery period, maximal and minimal key deliver time, and communication capacity for data collection are presented for various subscriber volume.

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Constructing Algorithm of Edge-Disjoint Spanning Trees in Even Interconnection Network Ed (이븐 연결망 Ed의 에지 중복 없는 스패닝 트리를 구성하는 알고리즘)

  • Kim, Jong-Seok;Kim, Sung-Won
    • The KIPS Transactions:PartA
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    • v.17A no.3
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    • pp.113-120
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    • 2010
  • Even networks were introduced as a class of fault-tolerant multiprocessor networks and analyzed so many useful properties and algorithms such as simple routing algorithms, maximal fault tolerance, node disjoint path. Introduced routing algorithms and node disjoint path algorithms are proven to be optimal. However, it has not been introduced to constructing scheme for edge-disjoint spanning trees in even networks. The design of edge-disjoint spanning trees is a useful scheme to analyze for measuring the efficiency of fault tolerant of interconnection network and effective broadcasting. Introduced routing algorithm or node disjoint path algorithm are for the purpose of routing or node disjoint path hence they are not applicable to constitute edge disjoint spanning tree. In this paper, we show a construction algorithm of edge-disjoint spanning trees in even network $E_d$.

Stereoscopic Image Generation with Optimal Disparity using Depth Map Preprocessing and Depth Information Analysis (깊이맵의 전처리와 깊이 정보의 기하학적 분석을 통한 최적의 스테레오스코픽 영상 자동 생성 기법)

  • Lee, Jae-Ho;Kim, Chang-Ick
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.164-177
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    • 2009
  • The DIBR(depth image-based rendering) method gives the sense of depth to viewers by using one color image and corresponding depth image. At this time, the qualities of the generated left- and right-image depend on the baseline distance of the virtual cameras corresponding to the view of the generated left- and right-image. In this paper, we present a novel method for enhancing the sense of depth by adjusting baseline distance of virtual cameras. Geometric analysis shows that the sense of depth is better in accordance with the increasing disparity due to the reduction of the image distortion. However, the entailed image degradation is not considered. Experimental results show that there is maximum bound in the disparity increasement due to image degradation and the visual field. Since the image degradation is reduced for increasing that bound, we add a depth map preprocessing. Since the interactive service where the disparity and view position are controlled by viewers can also be provided, the proposed method can be applied to the mobile broadcasting system such as DMB as well as 3DTV system.

Real-time Intelligent Exit Path Indicator Using BLE Beacon Enabled Emergency Exit Sign Controller

  • Jung, Joonseok;Kwon, Jongman;Jung, Soonho;Lee, Minwoo;Mariappan, Vinayagam;Cha, Jaesang
    • International journal of advanced smart convergence
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    • v.6 no.1
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    • pp.82-88
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    • 2017
  • Emergency lights and exit signs are an indispensable part of safety precautions for effective evacuation in case of emergency in public buildings. These emergency sign indicates safe escape routes and emergency doors, using an internationally recognizable sign. However visibility of those signs drops drastically in case of emergency situations like fire smoke, etc. and loss of visibility causes serious problems for safety evacuation. This paper propose a novel emergency light and exit sign built-in with Bluetooth Low Energy (BLE) Beacon to assist the emergency self-guiding evacuation using devices for crisis and emergency management to avoid panic condition inside the buildings. In this approach, the emergency light and exit sign with the BLE beacons deployed in the indoor environments and the smart devices detect their indoor positions, direction to move, and next exit sign position from beacon messages and interact with map server in the Internet / Intranet over the available LTE and/or Wi-Fi network connectivity. The map server generate an optimal emergency exit path according to the nearest emergency exit based on a novel graph generation method for less route computation for each smart device. All emergency exit path data interfaces among three system components, the emergency exit signs, map server, and smart devices, have been defined for modular implementation of our emergency evacuation system. The proposed exit sign experimental system has been deployed and evaluated in real-time building environment thoroughly and gives a good evidence that the modular design of the proposed exit sign system and a novel approach to compute emergency exit path route based on the BLE beacon message, map server, and smart devices is competitive and viable.

An Efficient Variant of Self-Healing Group Key Distribution Scheme with Revocation Capability (자가 치료 기능과 취소 능력을 가진 효율적인 그룹키 분배 기법)

  • Kang Ju-Sung;Hong Dowon
    • The KIPS Transactions:PartC
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    • v.12C no.7 s.103
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    • pp.941-948
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    • 2005
  • In the self-healing group key distribution scheme, users are capable of recovering lost group keys on their own without requesting additional transmission from the group manager, where there is no reliable network infrastructure. In this paper, we propose a new self-healing group key distribution scheme with revocation capability, which is optimal in terms of user memory storage and more efficient in terms of communication complexity than the previous results. We obtain a slightly improved result from (13) and (14) by using the new broadcasting method. In addition, we prove that our scheme has the properties of t-wise forward secrecy and t-wise backward secrecy, and extend this self-healing approach to the session key recovery scheme from a single broadcast message.

2D ECG Compression Using Optimal Sorting Scheme (정렬과 평균 정규화를 이용한 2D ECG 신호 압축 방법)

  • Lee, Kyu-Bong;Joo, Young-Bok;Han, Chan-Ho;Huh, Kyung-Moo;Park, Kil-Houm
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.4
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    • pp.23-27
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    • 2009
  • In this paper, we propose an effective compression method for electrocardiogram (ECG) signals. 1-D ECG signals are reconstructed to 2-D ECG data by period and complexity sorting schemes with image compression techniques to increase inter and intra-beat correlation. The proposed method added block division and mean-period normalization techniques on top of conventional 2-D data ECG compression methods. JPEG 2000 is chosen for compression of 2-D ECG data. Standard MIT-BIH arrhythmia database is used for evaluation and experiment. The results show that the proposed method outperforms compared to the most recent literature especially in case of high compression rate.