• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3353-3370
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• 2016

The way of combination of Product Perfect Codes (PPCs) is based on the theory of short codes constructing long codes. PPCs have larger embedding rate than Hamming codes by expending embedding columns in a coding block, and they have been proven to enhance the performance of the F₅ steganographic method. In this paper, the proposed modified product codes called MPCs are introduced as an efficient way to embed more data than PPCs by increasing 2^r₂-1-r₂ embedding columns. Unlike PPC, the generation of the check matrix H in MPC is random, and it is different from PPC. In addition a simple solving way of the linear algebraic equations is applied to figure out the problem of expending embedding columns or compensating cases. Furthermore, the MPCs over ℤ₄ have been proposed to further enhance not only the performance but also the computation speed which reaches O(n₁+σ). Finally, the proposed ℤ₄-MPC intends to maximize the embedding rate with maintaining less distortion , and the performance surpasses the existing improved product perfect codes. The performance of large embedding rate should have the significance in the high-capacity of covert communication.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.552-559
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• 2013

In this paper, the multiple-input multiple-output (MIMO) system with a precoder is considered in the transmit-correlated Rayleigh channels. We specifically target the MIMO system employing the minimum mean square error receivers. Based on random matrix theory, we first present a direct and generalized formulation for deriving a probability density function (PDF) of the signal-to-interference-plus-noise ratio (SINR). Then, we derive the accurate closed-form SINR PDFs for a small number of transmit and receive antennas. Based on the SINR PDFs, tight closed-form approximations of the symbol error rate (SER) are derived. Our analysis suggests that the SER approximations can be used to accurately estimate the error probabilities or as a useful tool for the system design.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.493-501
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• 2016

In-network storage is an effective technique for avoiding network congestion and reducing power consumption in continuous data collection in wireless sensor networks. In recent years, network coding based storage design has been proposed as a means to achieving ubiquitous access that permits any query to be satisfied by a few random (nearby) storage nodes. To maintain data consistency in continuous data collection applications, the readings of a sensor over time must be sent to the same set of storage nodes. In this paper, we present an efficient approach to updating data at storage nodes to maintain data consistency at the storage nodes without decoding out the old data and re-encoding with new data. We studied a transmission strategy that identifies a set of storage nodes for each source sensor that minimizes the transmission cost and achieves ubiquitous access by transmitting sparsely using the sparse matrix theory. We demonstrate that the problem of minimizing the cost of transmission with coding is NP-hard. We present an approximation algorithm based on regarding every storage node with memory size B as B tiny nodes that can store only one packet. We analyzed the approximation ratio of the proposed approximation solution, and compared the performance of the proposed coding approach with other coding schemes presented in the literature. The simulation results confirm that significant performance improvement can be achieved with the proposed transmission strategy.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.37-48
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• 2020

Purpose - This study empirically investigates whether the risk property included in fat-tails of return distributions is systematic or unsystematic based on the devised statistical methods. Design/methodology/approach - This study devised empirical designs based on two traditional methods: principal component analysis (PCA) and the testing method of portfolio diversification effect. The fatness of the tails in return distributions is quantitatively measured by statistical probability. Findings - According to the results, the risk property in the fat-tails of return distributions has the economic meanings of eigenvalues having a value greater than 1 through PCA, and also systematic risk that cannot be removed through portfolio diversification. In other words, the fat-tails of return distributions have the properties of the common factors, which may explain the changes of stock returns. Meanwhile, the fatness of the tails in the portfolio return distributions shows the asymmetric relationship of common factors on the tails of return distributions. The negative tail in the portfolio return distribution has a much closer relation with the property of common factors, compared to the positive tail. Research implications or Originality - This empirical evidence may complement the existing studies related to tail risk which is utilized in pricing models as a common factor.

• Steel and Composite Structures
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• v.51 no.1
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• pp.73-91
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• 2024

This paper has focused on presenting vibration analysis of trapezoidal sandwich plates with a damaged core and FG wavy CNT-reinforced face sheets. A damage model is introduced to provide an analytical description of an irreversible rheological process that causes the decay of the mechanical properties, in terms of engineering constants. An isotropic damage is considered for the core of the sandwich structure. The classical theory concerning the mechanical efficiency of a matrix embedding finite length fibers has been modified by introducing the tube-to-tube random contact, which explicitly accounts for the progressive reduction of the tubes' effective aspect ratio as the filler content increases. The First-order shear deformation theory of plate is utilized to establish governing partial differential equations and boundary conditions for the trapezoidal plate. The governing equations together with related boundary conditions are discretized using a mapping-generalized differential quadrature (GDQ) method in spatial domain. Then natural frequencies of the trapezoidal sandwich plates are obtained using GDQ method. Validity of the current study is evaluated by comparing its numerical results with those available in the literature. After demonstrating the convergence and accuracy of the method, different parametric studies for laminated trapezoidal structure including carbon nanotubes waviness (0≤w≤1), CNT aspect ratio (0≤AR≤4000), face sheet to core thickness ratio (0.1 ≤ ${\frac{h_f}{h_c}}$ ≤ 0.5), trapezoidal side angles (30° ≤ α, β ≤ 90°) and damaged parameter (0 ≤ D < 1) are carried out. It is explicated that the damaged core and weight fraction, carbon nanotubes (CNTs) waviness and CNT aspect ratio can significantly affect the vibrational behavior of the sandwich structure. Results show that by increasing the values of waviness index (w), normalized natural frequency of the structure decreases, and the straight CNT (w=0) gives the highest frequency. For an overall comprehension on vibration of laminated trapezoidal plates, some selected vibration mode shapes were graphically represented in this study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1102-1109
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• 2013

Blind interference alignment (BIA) scheme has demonstrated a way of interference alignment (IA) without channel state information at transmitter (CSIT). While it shows superior performance in high signal-to-noise ratio (SNR) regime stemming from the maximal degrees of freedom (DoF) gain, BIA scheme achieves inferior sum-rate performance in low SNR regime. This paper proposes a dual-mode transmission strategy which switches between single user (SU) SISO with receive mode selection and the BIA scheme depending upon the range of SNR. First, we derive a closed-form achievable rate for each transmission-mode. Secondly, we propose a low-complex transmission-mode selection algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.997-1004
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• 2015

In this paper, we study vertical sectorization techniques in multiple-input single-output (MISO) downlink active antenna systems (AAS). In the AAS, antenna beam patterns can be adjusted in each sector and multiple vertical beams can form the vertical sectorization. Since an exhaustive search based vertical sectorization algorithm requires high computational complexity to find the optimal tilt angles, we propose two vertical sectorization algorithms to reduce the complexity. First, we provide an asymptotic sum rate based algorithm which utilizes a large system approximation of the average sum rate based on the random matrix theory. Next, by using the result in the single sector transmission, the single sector based algorithm is proposed. In the simulation results, we confirm that the proposed algorithms are close to the performance of the exhaustive search algorithm with much reduced complexity.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.272-275
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• 2014

An improved fuzzy Kalman filtering speed estimation scheme was proposed by means of measuring stator side voltage and current value based on vector control state equation of induction motor. The designed fuzzy adaptive controller conducted recursive online correction of measurement noise covariance matrix by monitoring the ratio of theory residuals and actual residuals to make it approach real noise level gradually, allowing the filter to perform optimal estimation to improve estimation accuracy of EKF. Meanwhile, co-simulation scheme based on MATLAB and Ansoft was proposed in order to improve simulation accuracy. Field-circuit coupling problems of induction motor under the action of vector control were solved and the parameter optimization accuracy was improved dramatically. The simulation and experimental results show that this algorithm has a strong ability to inhibit the random measurement noise. It is able to estimate motor speed accurately, and has superior static and dynamic characteristics.

• International Journal of Oral Biology
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• v.43 no.2
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• pp.101-111
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• 2018

Understanding the classification of malocclusion is a crucial issue in Orthodontics. It can also help us to diagnose, treat, and understand malocclusion to establish a standard for definite class of patients. Principal component analysis (PCA) and k-means algorithms have been emerging as data analytic methods for cephalometric measurements, due to their intuitive concepts and application potentials. This study analyzed the macro- and meso-scale classification structure and feature basis vectors of 1020 (415 male, 605 female; mean age, 25 years) orthodontic patients using statistical preprocessing, PCA, random matrix theory (RMT) and k-means algorithms. RMT results show that 7 principal components (PCs) are significant standard in the extraction of features. Using k-means algorithms, 3 and 6 clusters were identified and the axes of PC1~3 were determined to be significant for patient classification. Macro-scale classification denotes skeletal Class I, II, III and PC1 means anteroposterior discrepancy of the maxilla and mandible and mandibular position. PC2 and PC3 means vertical pattern and maxillary position respectively; they played significant roles in the meso-scale classification. In conclusion, the typical patient profile (TPP) of each class showed that the data-based classification corresponds with the clinical classification of orthodontic patients. This data-based study can provide insight into the development of new diagnostic classifications.