Author Search Result

[Author] Atsushi IWASAKI(3hit)

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  • Handover with Proactive Anchor Router Relocation and Data Buffering

    Shin-ichi ISOBE  Atsushi IWASAKI  Ken IGARASHI  Masami YABUSAKI  

     
    PAPER-Mobility Management

      Vol:
    E87-B No:5
      Page(s):
    1193-1201

    This paper proposes "Handover with Proactive Anchor Router Relocation and Data Buffering" to suppress packet loss and packet miss-ordering during handover. To prevent packet miss-ordering, anchor router is proactively relocated to the optimal position before the mobile terminal performs handover. And, to eliminate packet loss during handover, anchor router buffers the packet only during handover. Moreover, anchor router assigns sequential numbers to the buffered packets to eliminate duplicate packet reception. Simulation results show that our proposal eliminates packet miss-ordering and duplicate reception while preventing packet loss.

  • Randomness Test to Solve Discrete Fourier Transform Test Problems

    Atsushi IWASAKI  Ken UMENO  

     
    PAPER-Cryptography and Information Security

      Vol:
    E101-A No:8
      Page(s):
    1204-1214

    The Discrete Fourier Transform Test (DFTT) is a randomness test in NIST SP800-22. However, to date, the theoretical reference distribution of the DFTT statistic has not been derived, which is problematic. We propose a new test using power spectrum variance as the test statistic whose reference distribution can be derived theoretically. Note that the purpose of both the DFTT and the proposed test is to detect periodic features. Experimental results demonstrate that the proposed test has stronger detection power than the DFTT and that it test can be used even for short sequences.

  • Does Reinforcement Learning Simulate Threshold Public Goods Games?: A Comparison with Subject Experiments

    Atsushi IWASAKI  Shuichi IMURA  Sobei H. ODA  Itsuo HATONO  Kanji UEDA  

     
    PAPER

      Vol:
    E86-D No:8
      Page(s):
    1335-1343

    This paper examines the descriptive power and the limitations of a simple reinforcement learning model (REL), comparing the simulation results with the results of an economic experiment employing human subjects. Agent-based computational economics and experimental economics are becoming increasingly popular as tools for economists. A new variety of learning model using games with a unique equilibrium is proposed and examined in both of the fields mentioned above. However, little attention is given to games with multiple equilibria. We examine threshold public goods games with two types of equilibria, where each player in a five-person group simultaneously contributes the public goods from her private endowments. In the experiments, we observe two patterns of the subjects' behavior: the cooperative and non-cooperative patterns. Our simulation results show that the REL reproduces the cooperative pattern, but does not reproduce the non-cooperative pattern. However, the results suggest that the REL does reproduce the non-cooperative pattern in terms of the agents' internal states. That implies that deterministic strategies would be required to reproduce the non-cooperative pattern in the games. We show an example of the REL with deterministic strategies.

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