The even-shift orthogonal sequence whose out-of-phase aperiodic autocorrelation function takes zero at any even shifts is generalized to multi-dimension called even-shift orthogonal array (E-array), and the logic function of E-array of power-of-two length is clarified. It is shown that E-array can be constructed by complementary arrays, which mean pairs of arrays that the sum of each aperiodic autocorrelation function at the same phase shifts takes zero at any shift except zero shift, as well as the one-dimensional case. It is also shown that the number of mates of E-array with which the cross correlation function between E-arrays takes zero at any even shifts is equal to the dimension. Furthermore it is investigated that E-array possesses good aperiodic autocorrelation that the rate of zero correlation values to array length approaches one as the dimension becomes large.

An instrument that can efficiently measure individual competency of IT applications (ICITA) is presented. It allows an organization to develop and manage the IT application capability of individuals working in an enterprise IT environment. The measurement items are generated from the definition and major components of individual competency of IT applications. The reliability and validity of the instrument construct are verified by factor and correlation analysis. A 15-item instrument is proposed to efficiently measure individual competency of IT applications and the instrument will contribute to the improved ICITA of human resources working in an enterprise IT environment.

In recent years, there has been an increasing demand with regard to available elemental services provided by independent firms for compositing new services. Currently, however, whenever it is difficult to maintain the required level of quality of a new composite web service, assignment of the new computer's resources as provisioning at the data center is not always effective, especially in the area of performance for composite web service providers. Thus, a new approach might be required. This paper presents a new control method aiming to maintain the performance requirements for composite web services. There are three aspects of our method that are applied: first of all, the theory of constraints (TOC) proposed by E.M. Goldratt ; secondly, an evaluation process in the non-linear feed forward controlling method: and finally multiple trials in applying policies with verification. In particular, we will discuss the architectural and theoretical aspects of the method in detail, and will show the insufficiency of combining the feedback controlling approach with TOC as a result of our evaluation.

Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the other known relations among the objects and to propose techniques called “PSD Estimation” and “Row Reduction” for the estimation problem. This technique uses a characteristic of the relations named “Positive Semi-Definiteness (PSD)” and a special assumption for known relations in a matrix. The superior performance of our approach in both efficiency and accuracy is demonstrated through an evaluation based on artificial and real-world data sets.

Blind source separation (BSS) techniques are required for various signal decomposing issues. Independent component analysis (ICA), assuming only a statistical independence among stochastic source signals, is one of the most useful BSS tools because it does not need a priori information on each source. However, there are many requirements for decomposing multiple deterministic signals such as complex sinusoidal signals with different frequencies. These requirements may include pulse compression or clutter rejection. It has been theoretically shown that an ICA algorithm based on maximizing non-Gaussianity successfully decomposes such deterministic signals. However, this ICA algorithm does not maintain a sufficient separation performance when the frequency difference of the sinusoidal waves becomes less than a nominal frequency resolution. To solve this problem, this paper proposes a super-resolution algorithm for complex sinusoidal signals by extending the maximum likelihood ICA, where the probability density function (PDF) of a complex sinusoidal signal is exploited as a priori knowledge, in which the PDF of the signal amplitude is approximated as a Gaussian distribution with an extremely small standard deviation. Furthermore, we introduce an optimization process for this standard deviation to avoid divergence in updating the reconstruction matrix. Numerical simulations verify that our proposed algorithm remarkably enhances the separation performance compared to the conventional one, and accomplishes a super-resolution separation even in noisy situations.

In LDMOS devices for high-voltage applications, there appears a notable fingerprint of current-voltage characteristics known as soft breakdown. Its mechanism is analyzed and modeled on LDMOS devices where a high resistive drift region exists. This analysis has revealed that the softness of breakdown, known as the expansion effect, withholding a run-away of current, is contributed by the flux of holes underneath the gate-overlap region originated by impact-ionization. The mechanism of the expansion effect is modeled and implemented into the compact model HiSIM_HV for circuit simulation. A good agreement between simulated characteristics and 2D-device simulation results is verified.

This paper proposes a new channel allocation algorithm for satellite communication systems. The algorithm is based on a spectrum division transmission technique as well as a spectrum compression transmission technique that we have developed in separate pieces of work. Using these techniques, the algorithm optimizes the spectrum bandwidth and a MODCOD (modulation and FEC error coding rate) scheme to balance the usable amount of satellite transponder bandwidth and satellite transmission power. Moreover, it determines the center frequency and bandwidth of each divided subspectra depending on the unused bandwidth of the satellite transponder bandwidth. As a result, the proposed algorithm enables flexible and effective usage of satellite resources (bandwidth and power) in channel allocations and thus enhances satellite communication (SATCOM) system capacity.

Limited Random Sequence (LRS) is quite important for Analog-to-Information Converter (AIC) because it determines the random sampling scheme and the resultant performance. LRS is established with the elements of “0” and “1”. The “1” appears randomly in the segment of the sequence, so that the production of the original signal and LRS can be considered as the approximation of the random sampling of the original signal. The random sampling result can perfectly recover the signal with Compressive Sensing (CS) algorithm. In this paper, a high order LRS is proposed for the AIC design in Distributed Compressive Sensing (DCS), which has the following three typical features: 1) The high order LRS has the elements of integer which can indicate the index number of the sensor in DCS. 2) High order LRS can adapt to the sparsity variation of the original signal detected by each sensor. 3) Employing the AIC with high order LRS, the DCS algorithm can recover the signal with very low sampling rate, usually above 2 orders less than the traditional distributed sensors. In the paper, the scheme and the construction algorithm of high order LRS are proposed. The performance is evaluated with the application studies of the distributed sensor network and the camera picture correspondingly.

In this paper, an imaging components transmission scheme for the improvement of multipath delay resolution in a Fractional Sampling (FS) OFDM receiver is proposed. FS has been proposed as a diversity scheme and achieves path diversity by enlarging the bandwidth of the baseband filters in order to transmit the imaging components of the desired signal. However, FS is not able to achieve diversity with very short delay multipaths because of its low multipath delay resolution. Wider bandwidth of the transmission signal is required to improve the resolution of the delay. On the other hand, cognitive radio is an emerging technology to utilize frequency spectrum flexibly through dynamic spectrum access (DSA). To resolve the small delay multipaths and to use the spectrum flexibly with DSA, this paper investigates the FS path diversity with the imaging components on the separated frequency channel. The correlation between the 2 FS branches is analyzed theoretically on the 2 path channel under the conditions of sampling interval, delay spread, and frequency separation. Numerical results through computer simulation show that the proposed scheme improves the multipath resolution and the bit error rate (BER) performance under the existence of small delay multipaths.

There are many web sites where net users can post and distribute their illustration images. A typical way to draw a digital illustration is first to draw rough lines on a paper and then to trace the lines on a graphics-tablet by hand. The input lines usually contain fluctuation due to hand-drawing, which limits the quality of illustration. Therefore, it is important to remove the fluctuation and to smooth the lines while maintaining sharp features such as corners. Although naive applications of moving average filters can smooth input lines, they may cause over-smoothing artifacts in which sharp features are lost by the filtering. This paper describes an improved line smoothing method using adaptive moving averages, which smoothes input lines while keeping high curvature points. The proposed method evaluates curvatures of input lines and adaptively controls the filter-size to reduce the over-smoothing artifacts. Experiments demonstrated advantages of the proposed method over the previous method in terms of achieving smoothing effect while still preserving sharp feature preservation.

Bipolar complementary sequence pairs of Types II and III are defined, enumerated for n ≤ 28, and classified. Type-II pairs are shown to exist only at lengths 2m, and necessary conditions for Type-III pairs lead to a non-existence conjecture regarding their length.

Compressing a JPEG image twice will greatly decrease the values of some of its DCT coefficients. This effect can be easily detected by statistics methods. To defend this forensic method, we establish a model to evaluate the security and image quality influenced by the re-compression. Base on the model, an optimized adjustment of the DCT coefficients is achieved by Genetic Algorithm. Results show that the traces of double compression are removed while preserving image quality.

Nowadays, there are a great deal of e-documents being accessed on the Internet. It would be helpful if those documents and significant extract contents could be automatically analyzed. Similarity analysis and topic extraction are widely used as document relation analysis techniques. Most of the methods being proposed need some processes such as stemming, stop words removal, and etc. In those methods, natural language processing (NLP) technology is necessary and hence they are dependent on the language feature and the dataset. In this study, we propose novel document relation analysis and topic extraction methods based on text compression. Our proposed approaches do not require NLP, and can also automatically evaluate documents. We challenge our proposal with model documents, URCS and Reuters-21578 dataset, for relation analysis and topic extraction. The effectiveness of the proposed methods is shown by the simulations.

The Internet infrastructure is evolving with various approaches such as cloud computing. Interest in cloud computing is growing with the rise of services and applications particularly in business community. For delivering service securely, cloud computing providers are facing several security issues, including controlling access to services and ensuring privacy. Most of access control approaches tend to a centralization of policy administration and decision by introducing a mediator central third party. However, with the growth of the Internet and the increase of cloud computing providers, a centralized administration is no longer supported. In this paper, we present a new collaborative access control infrastructure for distributed cloud computing environment, supporting collaborative delegations across multiple domains in order to authorize users to access services at a visited domain that does not have a direct cooperative relationship with the user's home domain. For this purpose, we propose an extension of the XACML (eXtensible Access Control Markup Language) model with a new entity called Delegation Validation Point (DVP) to support multi-domain delegation in a distributed environment. We describe the new extended model and functionalities of the new component. In addition, we define new XACML messages for acquiring delegation across domains. For exchanging delegation between domains we use SAML (Security Association Markup Language) and Diameter protocol. Two Diameter applications are defined for transporting securely multiple delegation requests and answers and for building a trusted path of cooperation to acquire the chain of delegations. We detail the implemented prototype and evaluate performance within a testbed of up to 20 domains.

Reverse-recovery modeling for p-i-n diodes in the high current-density conditions are discussed. With the dynamic carrier-distribution-based modeling approach, the reverse recovery behaviors are explained in the high current-density conditions, where the nonquasi-static (NQS) behavior of carriers in the drift region is considered. In addition, a specific feature under the high current-density condition is discussed. The proposed model is implemented into a commercial circuit simulator in the Verilog-A language and its reverse recovery modeling ability is verified with a two-dimensional (2D) device simulator, in comparison to the conventional lumped-charge modeling technique.

Computational Fluid Dynamics (CFD) is used as a common design tool in the aerospace industry. UPACS, a package for CFD, is convenient for users, since a customized simulator can be built just by selecting desired functions. The problem is its computation speed, which is difficult to enhance by using the clusters due to its complex memory access patterns. As an economical solution, accelerators using FPGAs are hopeful candidate. However, the total scale of UPACS is too large to be implemented on small numbers of FPGAs. For cost efficient implementation, partial reconfiguration which dynamically loads only required functions is proposed in this paper. Here, the MUSCL scheme, which is used frequently in UPACS, is selected as a target. Partial reconfiguration is applied to the flux limiter functions (FLF) in MUSCL. Four FLFs are implemented for Turbulence MUSCL (TMUSCL) and eight FLFs are for Convection MUSCL (CMUSCL). All FLFs are developed independently and separated from the top MUSCL module. At start-up, only required FLFs are selected and deployed in the system without interfering the other modules. This implementation has successfully reduced the resource utilization by 44% to 63%. Total power consumption also reduced by 33%. Configuration speed is improved by 34-times faster as compared to full reconfiguration method. All implemented functions achieved at least 17 times speed-up performance compared with the software implementation.

This letter deals with a system identification problem with unknown model order, which can be formulated as the matrix rank minimization problem by applying the subspace identification method. A sequential rank minimization algorithm is provided by modifying the null space based alternating optimization (NSAO) algorithm, and a model order identification algorithm is proposed. Numerical examples show that the proposed sequential algorithm can adaptively identify the model order of switched systems whose model order changes.

In this letter we design a new family of space-time block codes (STBC) for multi-input multi-output (MIMO) systems. The complex orthogonal STBC achieves full diversity and full transmission rate with fast maximum-likelihood decoding when only two transmit antennas are employed. By combining the Alamouti STBC and the multidimensional signal constellation rotation based on the cyclotomic number field, we construct cyclotomic orthogonal space-time block codes (COSTBCs) which can achieve full diversity and full rate for multiple transmit antennas. Theoretical analysis and simulation results demonstrate excellent performance of the proposed codes, while the decoding complexity is further reduced.

This paper proposes a verification-aware design methodology that provides developers with a systematic and reliable approach to performing thread-pipelining parallelization on sequential programs. In contrast to traditional design flow, a behavior-model program is constructed before parallelizing as a bridge to help developers gradually leverage the technique of thread-pipelining parallelization. The proposed methodology integrates verification mechanisms into the design flow. To demonstrate the practicality of the proposed methodology, we applied it to the parallelization of a 3D depth map generator with thread pipelining. The parallel 3D depth map generator was further integrated into a 3D video playing system for evaluation of the verification overheads of the proposed methodology and the system performance. The results show the parallel system can achieve 33.72 fps in D1 resolution and 12.22 fps in HD720 resolution through a five-stage pipeline. When verifying the parallel program, the proposed verification approach keeps the performance degradation within 23% and 21.1% in D1 and HD720 resolutions, respectively.

We propose a deception mechanism to combat a compromised station in IEEE 802.11 channel hopping systems. A compromised station can follow the hopping channels and continuously attack them, since it recognizes the channel-hopping sequence. The key concept of the deception mechanism is that an access point notifies a new hopping seed but not to the jammer, while a deception station deceives the jammer. Simulations show that the proposed scheme increases network throughput compared to conventional channel hopping schemes when they are under compromised station attacks.