• Title/Summary/Keyword: Complexity Analysis

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Computation and Communication Efficient Key Distribution Protocol for Secure Multicast Communication

  • Vijayakumar, P.;Bose, S.;Kannan, A.;Jegatha Deborah, L.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.4
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    • pp.878-894
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    • 2013
  • Secure multimedia multicast applications involve group communications where group membership requires secured dynamic key generation and updating operations. Such operations usually consume high computation time and therefore designing a key distribution protocol with reduced computation time is necessary for multicast applications. In this paper, we propose a new key distribution protocol that focuses on two aspects. The first one aims at the reduction of computation complexity by performing lesser numbers of multiplication operations using a ternary-tree approach during key updating. Moreover, it aims to optimize the number of multiplication operations by using the existing Karatsuba divide and conquer approach for fast multiplication. The second aspect aims at reducing the amount of information communicated to the group members during the update operations in the key content. The proposed algorithm has been evaluated based on computation and communication complexity and a comparative performance analysis of various key distribution protocols is provided. Moreover, it has been observed that the proposed algorithm reduces the computation and communication time significantly.

Conceptual Design Optimization of Tensairity Girder Using Variable Complexity Modeling Method

  • Yin, Shi;Zhu, Ming;Liang, Haoquan;Zhao, Da
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.1
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    • pp.29-36
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    • 2016
  • Tensairity girder is a light weight inflatable fabric structural concept which can be used in road emergency transportation. It uses low pressure air to stabilize compression elements against buckling. With the purpose of obtaining the comprehensive target of minimum deflection and weight under ultimate load, the cross-section and the inner pressure of tensairity girder was optimized in this paper. The Variable Complexity Modeling (VCM) method was used in this paper combining the Kriging approximate method with the Finite Element Analysis (FEA) method, which was implemented by ABAQUS. In the Kriging method, the sample points of the surrogate model were outlined by Design of Experiment (DOE) technique based on Optimal Latin Hypercube. The optimization framework was constructed in iSIGHT with a global optimization method, Multi-Island Genetic Algorithm (MIGA), followed by a local optimization method, Sequential Quadratic Program (SQP). The result of the optimization gives a prominent conceptual design of the tensairity girder, which approves the solution architecture of VCM is feasible and efficient. Furthermore, a useful trend of sensitivity between optimization variables and responses was performed to guide future design. It was proved that the inner pressure is the key parameter to balance the maximum Von Mises stress and deflection on tensairity girder, and the parameters of cross section impact the mass of tensairity girder obviously.

Design of Low Complexity Human Anxiety Classification Model based on Machine Learning (기계학습 기반 저 복잡도 긴장 상태 분류 모델)

  • Hong, Eunjae;Park, Hyunggon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.9
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    • pp.1402-1408
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    • 2017
  • Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

Measurement of program volume complexity using fuzzy self-organizing control (퍼지 적응 제어를 이용한 프로그램 볼륨 복잡도 측정)

  • 김재웅
    • Journal of the Korea Computer Industry Society
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    • v.2 no.3
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    • pp.377-388
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    • 2001
  • Software metrics provide effective methods for characterizing software. Metrics have traditionally been composed through the definition of an equation, but this approach restricted within a full understanding of every interrelationships among the parameters. This paper use fuzzy logic system that is capable of uniformly approximating any nonlinear function and applying cognitive psychology theory. First of all, we extract multiple regression equation from the factors of 12 software complexity metrics collected from Java programs. We apply cognitive psychology theory in program volume factor, and then measure program volume complexity to execute fuzzy learning. This approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics.

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Complexity and Algorithms for Optimal Bundle Search Problem with Pairwise Discount

  • Chung, Jibok;Choi, Byungcheon
    • Journal of Distribution Science
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    • v.15 no.7
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    • pp.35-41
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    • 2017
  • Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

Analysis of Joint Transmit and Receive Antenna Selection in CPM MIMO Systems

  • Lei, Guowei;Liu, Yuanan;Xiao, Xuefang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1425-1440
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    • 2017
  • In wireless communications, antenna selection (AS) is a widely used method for reducing comparable cost of multiple RF chains in MIMO systems. As is well known, most of literatures on combining AS with MIMO techniques concern linear modulations such as phase shift keying (PSK) and quadrature amplitude modulation (QAM). The combination of CPM and MIMO has been considered an optimal choice that can improve its capacity without loss of power and spectrum efficiency. The aim of this paper is to investigate joint transmit and receive antenna selection (JTRAS) in CPM MIMO systems. Specifically, modified incremental and decremental JTRAS algorithms are proposed to adapt to arbitrary number of selected transmit or receive antennas. The computational complexity of several JTRAS algorithms is analyzed from the perspective of channel capacity. As a comparison, the performances of bit error rate (BER) and spectral efficiency are evaluated via simulations. Moreover, computational complexity of the JTRAS algorithms is simulated in the end. It is inferred from discussions that both incremental JTRAS and decremental JTRAS perform close to optimal JTRAS in BER and spectral efficiency. In the sense of practical scenarios, adaptive JTRAS can be employed to well tradeoff performance and computational complexity.

A Prediction-based Energy-conserving Approximate Storage and Query Processing Schema in Object-Tracking Sensor Networks

  • Xie, Yi;Xiao, Weidong;Tang, Daquan;Tang, Jiuyang;Tang, Guoming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.5
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    • pp.909-937
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    • 2011
  • Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, a Prediction-based Energy-conserving Approximate StoragE schema (P-EASE) is proposed, which can reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. In addition, focusing on reducing the unnecessary querying messages, P-EASE enables an optimal query algorithm to taking into consideration to query the proper storage node, i.e., the nearer storage node of the centric storage node and local storage node. The theoretical analysis illuminates the correctness and efficiency of the P-EASE. Simulation experiments are conducted under semi-random walk and random waypoint mobility. Compared to EASE, P-EASE performs better at the query error, message complexity, total energy consumption and hotspot energy consumption. Results have shown that P-EASE is more energy-conserving and has higher location precision than EASE.

Analysis of Adaptive Digital Signal Processing for Anti-Jamming GPS System (Anti-Jamming GPS 시스템을 위한 적응형 디지털 신호 처리에 관한 분석)

  • Han, Jung-Su;Kim, Seok-Joong;Kim, Hyun-Do;Choi, Hyung-Jin;Kim, Ki-Yun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.8C
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    • pp.745-757
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    • 2007
  • In this paper, we propose a design of GPS anti-jamming system and its operational method, which can effectively suppress interference and jamming signals induced in GPS receiver. The 7-array antenna used in the proposed system is composed of conventional 6 equi-spaced circular elements with one element on the center of antenna and can be efficiently operated under power-constrained conditions. Futhermore, in this paper, we analyze the structure and complexity of STAP and SFAP which are well known techniques in adaptive array antenna signal processing, and we compare the BER performances between STAP and SFAP in various jamming environment based on the same complexity.

Battle Damage Analysis of Aircraft Wing Fuel Tanks by Hydrodynamic Ram Effect (항공기 날개 연료탱크의 수압램 전투손상 해석연구)

  • Kim, Jong-Heon;Jeon, Seung-Mun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.34 no.4
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    • pp.17-24
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    • 2006
  • Hydrodynamic ram of aircraft fuel tanks is one of main ballistic battle damages of an aircraft and has great importance to airframe survivability design. Basic concept, physics and research history of hydrodynamic ram are investigated. The penetration and internal detonation of a simple fuel tank and ICW(Intermediate Complexity Wing) are analyzed by computational method. Structural rupture and fluid burst are analytically realized using general coupling and coupling surface interaction. The results such as fluid pressure, tank stress and displacement are shown and future research chances are suggested based on the study.

A New Video Bit Rate Estimation Scheme using a Model for IPTV Services

  • Cho, Hye-Jeong;Noh, Dae-Young;Jang, Seong-Hwan;Kwon, Jae-Cheol;Oh, Seoung-Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.10
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    • pp.1814-1829
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    • 2011
  • In this paper, we present a model-based video bit rate estimation scheme for reducing the bit rate while maintaining a given target quality in many video streaming services limited by network bandwidth, such as IPTV services. Each item of video content can be stored on a video streaming server and delivered with the estimated bit rate using the proposed scheme, which consists of the following two steps: 1) In the first step, the complexity of each intra-frame in a given item of video content is computed as a frame feature to extract a group of candidate frames with a lot of bits. 2) In the second step, the bit rate of the video content is determined by applying statistical analysis and hypothesis testing to that group. The experimental results show that our scheme can reduce the bit rate by up to 78% with negligible degradation of subjective quality, especially with the low-complexity videos commonly used in IPTV services.