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4901-4920hit(42807hit)

  • 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.

  • Averaging Area of Incident Power Density for Human Exposure from Patch Antenna Arrays

    Daisuke FUNAHASHI  Takahiro ITO  Akimasa HIRATA  Takahiro IYAMA  Teruo ONISHI  

     
    BRIEF PAPER

      Vol:
    E101-C No:8
      Page(s):
    644-646

    This study discusses an area-averaged incident power density to estimate surface temperature elevation from patch antenna arrays with 4 and 9 elements at the frequencies above 10 GHz. We computationally demonstrate that a smaller averaging area (1 cm2) of power density should be considered at the frequency of 30 GHz or higher compared with that at lower frequencies (4 cm2).

  • Binary Sequence Pairs of Period pm-1 with Optimal Three-Level Correlation

    Lianfei LUO  Wenping MA  Feifei ZHAO  

     
    LETTER-Information Theory

      Vol:
    E101-A No:8
      Page(s):
    1263-1266

    Let Fpm be the field of pm elements where p is an odd prime. In this letter, binary sequence pairs of period N=pm-1 are presented, where sequences are generated from the polynomial x2-c for any c Fpm{0}. The cross-correlation values of sequence pairs are completely determined, our results show that those binary sequence pairs have optimal three-level correlation.

  • Multi-Channels LSTM Networks for Fence Activity Classification

    Kelu HU  Chunlei ZHENG  Wei HE  Xinghe BAO  Yingguan WANG  

     
    LETTER-Biocybernetics, Neurocomputing

      Pubricized:
    2018/04/23
      Vol:
    E101-D No:8
      Page(s):
    2173-2177

    We propose a novel neural networks model based on LSTM which is used to solve the task of classifying inertial sensor data attached to a fence with the goal of detecting security relevant incidents. To evaluate it we deployed an experimental fence surveillance system. By comparing experimental data of different approaches we find out that the neural network outperforms the baseline approach.

  • Safety Technologies in Autonomous Decentralized Railway Control System and its Future Studies Open Access

    Shinichi RYOKI  Takashi KUNIFUJI  Toshihiro ITOH  

     
    INVITED PAPER

      Pubricized:
    2018/02/22
      Vol:
    E101-B No:8
      Page(s):
    1768-1774

    Along with the sophistication of society, the requirements for infrastructure systems are also becoming more sophisticated. Conventionally, infrastructure systems have been accepted if they were safe and stable, but nowadays they are required for serviceability as a matter of course. For this reason, not only the expansion of the scope of the control system but also the integration with the information service system has been frequently carried out. In this paper, we describe safety technology based on autonomous decentralized technology as one of the measures to secure safety in a control system integrating such information service functions. And we propose its future studies.

  • An Emotion Similarity Based Severity Prediction of Software Bugs: A Case Study of Open Source Projects

    Geunseok YANG  Tao ZHANG  Byungjeong LEE  

     
    PAPER-Software Engineering

      Pubricized:
    2018/05/02
      Vol:
    E101-D No:8
      Page(s):
    2015-2026

    Many software development teams usually tend to focus on maintenance activities in general. Recently, many studies on bug severity prediction have been proposed to help a bug reporter determine severity. But they do not consider the reporter's expression of emotion appearing in the bug report when they predict the bug severity level. In this paper, we propose a novel approach to severity prediction for reported bugs by using emotion similarity. First, we do not only compute an emotion-word probability vector by using smoothed unigram model (UM), but we also use the new bug report to find similar-emotion bug reports with Kullback-Leibler divergence (KL-divergence). Then, we introduce a new algorithm, Emotion Similarity (ES)-Multinomial, which modifies the original Naïve Bayes Multinomial algorithm. We train the model with emotion bug reports by using ES-Multinomial. Finally, we can predict the bug severity level in the new bug report. To compare the performance in bug severity prediction, we select related studies including Emotion Words-based Dictionary (EWD)-Multinomial, Naïve Bayes Multinomial, and another study as baseline approaches in open source projects (e.g., Eclipse, GNU, JBoss, Mozilla, and WireShark). The results show that our approach outperforms the baselines, and can reflect reporters' emotional expressions during the bug reporting.

  • A Routing Method for Fish Farm Monitoring Under Short Transmission Range Condition

    Koichi ISHIDA  Yoshiaki TANIGUCHI  Nobukazu IGUCHI  

     
    LETTER-Information Network

      Pubricized:
    2018/05/16
      Vol:
    E101-D No:8
      Page(s):
    2145-2149

    We have proposed a fish farm monitoring system for achieving efficient fish farming. In our system, sensor nodes are attached at fish to monitor its health status. In this letter, we propose a method for gathering sensor data from sensor nodes to sink nodes when the transmission range of sensor node is shorter than the size of fish cage. In our proposed method, a part of sensor nodes become leader nodes and they forward gathered sensor data to the sink nodes. Through simulation evaluations, we show that the data gathering performance of our proposed method is higher than that of traditional methods.

  • Improved Radiometric Calibration by Brightness Transfer Function Based Noise & Outlier Removal and Weighted Least Square Minimization

    Chanchai TECHAWATCHARAPAIKUL  Pradit MITTRAPIYANURUK  Pakorn KAEWTRAKULPONG  Supakorn SIDDHICHAI  Werapon CHIRACHARIT  

     
    PAPER-Image Recognition, Computer Vision

      Pubricized:
    2018/05/16
      Vol:
    E101-D No:8
      Page(s):
    2101-2114

    An improved radiometric calibration algorithm by extending the Mitsunaga and Nayar least-square minimization based algorithm with two major ideas is presented. First, a noise & outlier removal procedure based on the analysis of brightness transfer function is included for improving the algorithm's capability on handling noise and outlier in least-square estimation. Second, an alternative minimization formulation based on weighted least square is proposed to improve the weakness of least square minimization when dealing with biased distribution observations. The performance of the proposed algorithm with regards to two baseline algorithms is demonstrated, i.e. the classical least square based algorithm proposed by Mitsunaga and Nayar and the state-of-the-art rank minimization based algorithm proposed by Lee et al. From the results, the proposed algorithm outperforms both baseline algorithms on both the synthetic dataset and the dataset of real-world images.

  • Transform Electric Power Curve into Dynamometer Diagram Image Using Deep Recurrent Neural Network

    Junfeng SHI  Wenming MA  Peng SONG  

     
    LETTER-Artificial Intelligence, Data Mining

      Pubricized:
    2018/05/09
      Vol:
    E101-D No:8
      Page(s):
    2154-2158

    To learn the working situation of rod-pumped wells under ground, we always need to analyze dynamometer diagrams, which are generated by the load sensor and displacement sensor. Rod-pumped wells are usually located in the places with extreme weather, and these sensors are installed on some special oil equipments in the open air. As time goes by, sensors are prone to generating unstable and incorrect data. Unfortunately, load sensors are too expensive to frequently reinstall. Therefore, the resulting dynamometer diagrams sometimes cannot make an accurate diagnosis. Instead, as an absolutely necessary equipment of the rod-pumped well, the electric motor has much longer life and cannot be easily impacted by the weather. The electric power curve during a swabbing period can also reflect the working situation under ground, but is much harder to explain than the dynamometer diagram. This letter presented a novel deep learning architecture, which can transform the electric power curve into the dimensionless dynamometer diagram image. We conduct our experiments on a real-world dataset, and the results show that our method can get an impressive transformation accuracy.

  • A Design for Testability of Open Defects at Interconnects in 3D Stacked ICs

    Fara ASHIKIN  Masaki HASHIZUME  Hiroyuki YOTSUYANAGI  Shyue-Kung LU  Zvi ROTH  

     
    PAPER-Dependable Computing

      Pubricized:
    2018/05/09
      Vol:
    E101-D No:8
      Page(s):
    2053-2063

    A design-for-testability method and an electrical interconnect test method are proposed to detect open defects occurring at interconnects among dies and input/output pins in 3D stacked ICs. As part of the design method, an nMOS and a diode are added to each input interconnect. The test method is based on measuring the quiescent current that is made to flow through an interconnect to be tested. The testability is examined both by SPICE simulation and by experimentation. The test method enabled the detection of open defects occurring at the newly designed interconnects of dies at experiments test speed of 1MHz. The simulation results reveal that an open defect generating additional delay of 279psec is detectable by the test method at a test speed of 200MHz beside of open defects that generate no logical errors.

  • An Efficient Misalignment Method for Visual Tracking Based on Sparse Representation

    Shan JIANG  Cheng HAN  Xiaoqiang DI  

     
    PAPER-Image Recognition, Computer Vision

      Pubricized:
    2018/05/14
      Vol:
    E101-D No:8
      Page(s):
    2123-2131

    Sparse representation has been widely applied to visual tracking for several years. In the sparse representation framework, tracking problem is transferred into solving an L1 minimization issue. However, during the tracking procedure, the appearance of target was affected by external environment. Therefore, we proposed a robust tracking algorithm based on the traditional sparse representation jointly particle filter framework. First, we obtained the observation image set from particle filter. Furthermore, we introduced a 2D transformation on the observation image set, which enables the tracking target candidates set more robust to handle misalignment problem in complex scene. Moreover, we adopt the occlusion detection mechanism before template updating, reducing the drift problem effectively. Experimental evaluations on five public challenging sequences, which exhibit occlusions, illuminating variations, scale changes, motion blur, and our tracker demonstrate accuracy and robustness in comparisons with the state-of-the-arts.

  • A New Interpretation of Physical Optics Approximation from Surface Equivalence Theorem

    Hieu Ngoc QUANG  Hiroshi SHIRAI  

     
    PAPER-Electromagnetic Theory

      Vol:
    E101-C No:8
      Page(s):
    664-670

    In this study, the electromagnetic scatterings from conducting bodies have been investigated via a surface equivalence theorem. When one formulates equivalent electric and magnetic currents from geometrical optics (GO) reflected field in the illuminated surface and GO incident field in the shadowed surface, it has been found that the asymptotically derived radiation fields are found to be the same as those formulated from physical optics (PO) approximation.

  • Proof and Evaluation of Improved Slack Reclamation for Response Time Analysis of Real-Time Multiprocessor Systems

    Hyeongboo BAEK  Donghyouk LIM  Jinkyu LEE  

     
    LETTER-Software System

      Pubricized:
    2018/05/02
      Vol:
    E101-D No:8
      Page(s):
    2136-2140

    RTA (Response time analysis) is a popular technique to guarantee timing requirements for a real-time system, and therefore the RTA framework has been widely studied for popular scheduling algorithms such as EDF (Earliest Deadline First) and FP (Fixed Priority). While a number of extended techniques of RTA have been introduced, some of them cannot be used since they have not been proved and evaluated in terms of their correctness and empirical performance. In this letter, we address the state of the art technique of slack reclamation of the existing generic RTA framework for multiprocessors. We present its mathematical proof of correctness and empirical performance evaluation, which have not been revealed to this day.

  • Performance Analysis of IEEE 802.11 DCF Based on a Macroscopic State Description

    Xiang LI  Yuki NARITA  Yuta GOTOH  Shigeo SHIODA  

     
    PAPER-Terrestrial Wireless Communication/Broadcasting Technologies

      Pubricized:
    2018/01/22
      Vol:
    E101-B No:8
      Page(s):
    1923-1932

    We propose an analytical model for IEEE 802.11 wireless local area networks (WLANs). The analytical model uses macroscopic descriptions of the distributed coordination function (DCF): the backoff process is described by a few macroscopic states (medium-idle, transmission, and medium-busy), which obviates the need to track the specific backoff counter/backoff stages. We further assume that the transitions between the macroscopic states can be characterized as a continuous-time Markov chain under the assumption that state persistent times are exponentially distributed. This macroscopic description of DCF allows us to utilize a two-dimensional continuous-time Markov chain for simplifying DCF performance analysis and queueing processes. By comparison with simulation results, we show that the proposed model accurately estimates the throughput performance and average queue length under light, heavy, or asymmetric traffic.

  • Dielectric Measurement in Liquids Using an Estimation Equation without Short Termination via the Cut-Off Circular Waveguide Reflection Method

    Kouji SHIBATA  

     
    PAPER

      Vol:
    E101-C No:8
      Page(s):
    627-636

    In this study, a theory for estimating the dielectric properties for unknown materials from three reference materials without using a short condition was developed. Specifically, the relationships linking the S parameter, electrostatic capacity, the measurement instrument and the jig were determined for four equivalent circuits with three reference materials and an unknown material inserted into the jig. An equation for estimation of complex permittivity from three reference materials without short termination was thus derived. The formula's accuracy was then numerically verified for cases in which values indicating the dielectric properties of the reference materials and the actual material differed significantly, thereby verifying the effectiveness of the proposed method. Next, it was also found that dielectric constant could be correctly determined even when the observation plane was moved to the SOL calibration plane on the generator side. The dielectric properties of various liquids in the 0.50, 1.0 and 2.5 GHz bands as measured using the proposed method were then compared with corresponding conventional-method values. Finally, the validity of the proposed method was also indicated by measurement values showing the frequency characteristics of dielectric properties at frequencies ranging from 0.50 to 3.0 GHz.

  • PCANet-II: When PCANet Meets the Second Order Pooling

    Chunxiao FAN  Xiaopeng HONG  Lei TIAN  Yue MING  Matti PIETIKÄINEN  Guoying ZHAO  

     
    LETTER-Pattern Recognition

      Pubricized:
    2018/05/14
      Vol:
    E101-D No:8
      Page(s):
    2159-2162

    PCANet, as one noticeable shallow network, employs the histogram representation for feature pooling. However, there are three main problems about this kind of pooling method. First, the histogram-based pooling method binarizes the feature maps and leads to inevitable discriminative information loss. Second, it is difficult to effectively combine other visual cues into a compact representation, because the simple concatenation of various visual cues leads to feature representation inefficiency. Third, the dimensionality of histogram-based output grows exponentially with the number of feature maps used. In order to overcome these problems, we propose a novel shallow network model, named as PCANet-II. Compared with the histogram-based output, the second order pooling not only provides more discriminative information by preserving both the magnitude and sign of convolutional responses, but also dramatically reduces the size of output features. Thus we combine the second order statistical pooling method with the shallow network, i.e., PCANet. Moreover, it is easy to combine other discriminative and robust cues by using the second order pooling. So we introduce the binary feature difference encoding scheme into our PCANet-II to further improve robustness. Experiments demonstrate the effectiveness and robustness of our proposed PCANet-II method.

  • Attribute-Based Keyword Search with Proxy Re-Encryption in the Cloud

    Yanli CHEN  Yuanyuan HU  Minhui ZHU  Geng YANG  

     
    PAPER-Fundamental Theories for Communications

      Pubricized:
    2018/02/16
      Vol:
    E101-B No:8
      Page(s):
    1798-1808

    This work is conducted to solve the current problem in the attribute-based keyword search (ABKS) scheme about how to securely and efficiently delegate the search rights to other users when the authorized user is not online. We first combine proxy re-encryption (PRE) with the ABKS technology and propose a scheme called attribute-based keyword search with proxy re-encryption (PABKS). The scheme not only realizes the functions of data search and fine-grained access control, but also supports search function sharing. In addition, we randomly blind the user's private key to the server, which ensures the confidentiality and security of the private key. Then, we also prove that the scheme is selective access structure and chosen keyword attack (IND-sAS-CKA) secured in the random oracle model. A performance analysis and security proof show that the proposed scheme can achieve efficient and secure data search in the cloud.

  • Facilitating Dynamic RT-QoS for Massive-Scale Autonomous Cyber-Physical Systems Open Access

    David W. McKEE  Xue OUYANG  Jie XU  

     
    INVITED PAPER

      Pubricized:
    2018/02/22
      Vol:
    E101-B No:8
      Page(s):
    1760-1767

    With the evolution of autonomous distributed systems such as smart cities, autonomous vehicles, smart control and scheduling systems there is an increased need for approaches to manage the execution of services to deliver real-time performance. As Cloud-hosted services are increasingly used to provide intelligence and analytic functionality to Internet of Things (IoT) systems, Quality of Service (QoS) techniques must be used to guarantee the timely service delivery. This paper reviews state-of-the-art QoS and Cloud techniques for real-time service delivery and data analysis. A review of straggler mitigation and a classification of real-time QoS techniques is provided. Then a mathematical framework is presented capturing the relationship between the host execution environment and the executing service allowing the response-times to predicted throughout execution. The framework is shown experimentally to reduce the number of QoS violations by 21% and provides alerts during the first 14ms provide alerts for 94% of future violations.

  • Detecting Unsafe Raw Pointer Dereferencing Behavior in Rust

    Zhijian HUANG  Yong Jun WANG  Jing LIU  

     
    LETTER-Dependable Computing

      Pubricized:
    2018/05/14
      Vol:
    E101-D No:8
      Page(s):
    2150-2153

    The rising systems programming language Rust is fast, efficient and memory safe. However, improperly dereferencing raw pointers in Rust causes new safety problems. In this paper, we present a detailed analysis into these problems and propose a practical hybrid approach to detecting unsafe raw pointer dereferencing behaviors. Our approach employs pattern matching to identify functions that can be used to generate illegal multiple mutable references (We define them as thief function) and instruments the dereferencing operation in order to perform dynamic checking at runtime. We implement a tool named UnsafeFencer and has successfully identified 52 thief functions in 28 real-world crates*, of which 13 public functions are verified to generate multiple mutable references.

  • Study on Single-Polarized Holey Fibers with Double-Hole Unit Cores for Cross-Talk Free Polarization Splitter

    Zejun ZHANG  Yasuhide TSUJI  Masashi EGUCHI  Chun-ping CHEN  

     
    PAPER

      Vol:
    E101-C No:8
      Page(s):
    620-626

    A single-polarization single-mode (SPSM) photonic crystal fiber (PCF) based on double-hole unit core is proposed in this paper for application to cross-talk free polarization splitter (PS). Birefringence of the PCF is obtained by adopting double-hole unit cells into the core to destroy its symmetry. With an appropriate cladding hole size, single x- or y-polarized PCF can be achieved by arranging the double-hole unit in the core along the x- or y-axis, respectively. Moreover, our proposed SPSM PCF has the potential to be applied to consist a cross-talk free PS. The simulation result by employing a vectorial finite element beam propagation method (FE-BPM) demonstrates that an arbitrary polarized incident light can be completely separated into two orthogonal single-polarized components through the PS. The structural tolerance and wavelength dependence of the PS have also been discussed in detail.

4901-4920hit(42807hit)