Avoiding runway incursions is a significant challenge and a top priority in aviation. Due to all causes of runway incursions belong to human factors, runway incursion prevention systems should remove human from the system operation loop as much as possible. Although current runway incursion prevention systems have made big progress on how to obtain accurate and sufficient information of aircraft/vehicles, they cannot predict and detect runway incursions as early as experienced air traffic controllers by using the same surveillance information, and cannot give explicit instructions and/or suggestions to prevent runway incursions like real air traffic controllers either. In one word, human still plays an important position in current runway incursion prevention systems. In order to remove human factors from the system operation loop as much as possible, this paper proposes a new type of runway incursion prevention system based on logic-based reasoning. The system predicts and detects runway incursions, then gives explicit instructions and/or suggestions to pilots/drivers to avoid runway incursions/collisions. The features of the system include long-range prediction of incidents, explicit instructions and/or suggestions, and flexible model for different policies and airports. To evaluate our system, we built a simulation system, and evaluated our system using both real historical scenarios and conventional fictional scenarios. The evaluation showed that our system is effective at providing earlier prediction of incidents than current systems, giving explicit instructions and/or suggestions for handling the incidents effectively, and customizing for specific policies and airports using flexible model.

Cloud computing is broadly recognized as as the prevalent trend in IT. However, in cloud computing mode, customers lose the direct control of their data and applications hosted by the cloud providers, which leads to the trustworthiness issue of the cloud providers, hindering the widespread use of cloud computing. This paper proposes a trustworthiness verification and audit mechanism on cloud providers called T-YUN. It introduces a trusted third party to cyclically attest the remote clouds, which are instrumented with the trusted chain covering the whole architecture stack. According to the main operations of the clouds, remote verification protocols are also proposed in T-YUN, with a dedicated key management scheme. This paper also implements a proof-of-concept emulator to validate the effectiveness and performance overhead of T-YUN. The experimental results show that T-YUN is effective and the extra overhead incurred by it is acceptable.

In an orthogonal frequency division multiplexing (OFDM) communication system, two users use the same frequencies and number of sub-carriers so as to increase spectrum efficiency. When the codewords employed by them form a Golay complementary sequence (CS) mate, this system enjoys the upper bound of peak-to-mean envelope power ratio (PMEPR) as low as 4. This letter presents a construction method for producing S16-QAM and A16-QAM Golay CS mates, which arrives at the upper bound 4 of PMEPR. And when used as a Golay CS pair, they have an upper bound 2 of PMEPR, which is the same ones in both [18] and [17]. However, both cannot produce such mates.

This paper proposes novel robust speech F0 estimation using Summation Residual Harmonics (SRH) based on TV-CAR (Time-Varying Complex AR) analysis. The SRH-based F0 estimation was proposed by A. Alwan, in which the criterion is calculated from LP residual signals. The criterion is summation of residual spectrum value for harmonics. In this paper, we propose SRH-based F0 estimation based on the TV-CAR analysis, in which the criterion is calculated from the complex AR residual. Since complex AR residual provides higher resolution of spectrum, it can be considered that the criterion is effective for F0 estimation. The experimental results demonstrate that the proposed method performs better than conventional methods; weighted auto-correlation and YIN.

To understand human emotion, it is necessary to be aware of the surrounding situation and individual personalities. In most previous studies, however, these important aspects were not considered. Emotion recognition has been considered as a classification problem. In this paper, we attempt new approaches to utilize a person's situational information and personality for use in understanding emotion. We propose a method of extracting situational information and building a personalized emotion model for reflecting the personality of each character in the text. To extract and utilize situational information, we propose a situation model using lexical and syntactic information. In addition, to reflect the personality of an individual, we propose a personalized emotion model using KBANN (Knowledge-based Artificial Neural Network). Our proposed system has the advantage of using a traditional keyword-spotting algorithm. In addition, we also reflect the fact that the strength of emotion decreases over time. Experimental results show that the proposed system can more accurately and intelligently recognize a person's emotion than previous methods.

This paper presents a VLSI design of a Tomlinson-Harashima (TH) precoder for multi-user MIMO (MU-MIMO) systems. The TH precoder consists of LQ decomposition (LQD), interference cancellation (IC), and weight coefficient multiplication (WCM) units. The LQ decomposition unit is based on an application specific instruction-set processor (ASIP) architecture with floating-point arithmetic for high accuracy operations. In the IC and WCM units with fixed-point arithmetic, the proposed architecture uses an arrayed pipeline structure to shorten a circuit critical path delay. The implementation result shows that the proposed architecture reduces circuit area and power consumption by 11% and 15%, respectively.

The most important advantage of HMM-based TTS is its highly intelligible. However, speech synthesized by HMM-based TTS is muffled and far from natural, especially under limited data conditions, which is mainly caused by its over-smoothness. Therefore, the motivation for this paper is to improve the naturalness of HMM-based TTS trained under limited data conditions while preserving its intelligibility. To achieve this motivation, a hybrid TTS between HMM-based TTS and the modified restricted Temporal Decomposition (MRTD), named HTD in this paper, was proposed. Here, TD is an interpolation model of decomposing a spectral or prosodic sequence of speech into sparse event targets and dynamic event functions, and MRTD is one simplified version of TD. With a determination of event functions close to the concept of co-articulation in speech, MRTD can synthesize smooth speech and the smoothness in synthesized speech can be adjusted by manipulating event targets of MRTD. Previous studies have also found that event functions of MRTD can represent linguistic information of speech, which is important to perceive speech intelligibility, while sparse event targets can convey the non-linguistics information, which is important to perceive the naturalness of speech. Therefore, prosodic trajectories and MRTD event functions of the spectral trajectory generated by HMM-based TTS were kept unchanged to preserve the high and stable intelligibility of HMM-based TTS. Whereas MRTD event targets of the spectral trajectory generated by HMM-based TTS were rendered with an original speech database to enhance the naturalness of synthesized speech. Experimental results with small Vietnamese datasets revealed that the proposed HTD was equivalent to HMM-based TTS in terms of intelligibility but was superior to it in terms of naturalness. Further discussions show that HTD had a small footprint. Therefore, the proposed HTD showed its strong efficiency under limited data conditions.

In this paper, we consider the problem of inferring a Boolean network (BN) from a given set of singleton attractors, where it is required that the resulting BN has the same set of singleton attractors as the given one. We show that the problem can be solved in linear time if the number of singleton attractors is at most two and each Boolean function is restricted to be a conjunction or disjunction of literals. We also show that the problem can be solved in polynomial time if more general Boolean functions can be used. In addition to the inference problem, we study two network completion problems from a given set of singleton attractors: adding the minimum number of edges to a given network, and determining Boolean functions to all nodes when only network structure of a BN is given. In particular, we show that the latter problem cannot be solved in polynomial time unless P=NP, by means of a polynomial-time Turing reduction from the complement of the another solution problem for the Boolean satisfiability problem.

In this paper, Hermite polynomial representation is proposed as an alternative way to represent finite fields of characteristic two. We show that multiplication in Hermite polynomial representation can be achieved with subquadratic space complexity. This representation enables us to find binomial or trinomial irreducible polynomials which allows us faster modular reduction over binary fields when there is no desirable such low weight irreducible polynomial in other representations. We then show that the product of two elements in Hermite polynomial representation can be performed as Toeplitz matrix-vector product. This representation is very interesting for NIST recommended binary field GF(2571) since there is no ONB for the corresponding extension. This representation can be used to obtain more efficient finite field arithmetic.

Many fatal accidents involving safety-critical reactive systems have occurred in unexpected situations, which were not considered during the design and test phases of system development. To prevent such accidents, reactive systems should be designed to respond appropriately to any request from an environment at any time. Verifying this property during the specification phase reduces the development costs of safety-critical reactive systems. This property of a specification is commonly known as realizability. The complexity of the realizability problem is 2EXPTIME-complete. We have introduced the concept of strong satisfiability, which is a necessary condition for realizability. Many practical unrealizable specifications are also strongly unsatisfiable. In this paper, we show that the complexity of the strong satisfiability problem is EXPSPACE-complete. This means that strong satisfiability offers the advantage of lower complexity for analysis, compared to realizability. Moreover, we show that the strong satisfiability problem remains EXPSPACE-complete even when only formulae with a temporal depth of at most 2 are allowed.

This paper contributes to k-error linear complexity of some generalized cyclotomic binary sequences of length 2pm and pm constructed in recent years. By defining related reference sequences, we find that these sequences possess very low k-error linear complexity for some certain values of the parameter k even though they have high linear complexity. Moreover, we point out that (p-1)-tuple distributions of all these sequences are not span. Thus they should be selected carefully for use in stream cipher systems.

In this paper, a multi-temporal analysis of polarimetric synthetic aperture radar (Pol-SAR) data over the sandbank and oyster farm area is presented. Specifically, a four-component scattering model, being able to identify single bounce, double bounce, volume, and helix scattering power contributions, has been employed to retrieve information. Decomposition results of a time series RADARSAT Pol-SAR images acquired over the western Taiwan coast indicate that the coastal tide level plays a key role in the sandbank and oyster farm monitoring. At high tide levels, the underlying sandbank creates a shallow area with an increased roughness of the above sea surface, leading to an enhanced surface scattering power as compared to the ambient water. Contrarily, at low tide levels, the exposed sandbank appears to be a smooth scatterer, generating decreased backscattering power than the surrounding area. On the other hand, the double-bounce scattering power is shown to be highly correlated with the tide level in the oyster farms due to their vertical structures. This also demonstrates a promising potential of the four-component scattering power decomposition for coastal tide level monitoring applications.

The optimal design of an extrapolated impulse response (EIR) filter (in the mini-max sense) is a non-linear programming problem. In this paper, the optimal design of the EIR filter by the semi-infinite programming (SIP) is investigated and an iterative technique for optimally designing the EIR filter is proposed. The simulation experiment validates the effectiveness of the SIP technique and the proposed iterative technique in the optimal design of the EIR filter.

In this paper, we propose periodic and aperiodic security limits for compromising emanations in the VHF and UHF bands. First, we perform the electromagnetic emanation security (EMSEC)-channel measurements in the 200-1000MHz frequency bands. Second, we analyse the pathloss characteristics of the indoor EMSEC-channel based on these measurements. Through this EMSEC-channel analysis, we affirm that the total radio attenuation, which is one of the key parameters for determining the security limits for compromising emanations, follows the Rician distribution. With these results, we propose that periodic and aperiodic emission security limits can be classified into two levels depending on the total radio attenuation and the extent of required confidentiality. The proposed security limits are compared with other security limits and existing civil and military EMC standards.

In the recently developed Flexible Wireless System (FWS), the same platform needs to deal with different wireless systems. This increases nonlinear distortion in its wideband power amplifier (PA) because the PA needs to concurrently amplify multi-band signals. By taking higher harmonics as well as inter- and cross-modulation distortion into consideration, we have developed a method to analytically evaluate the adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) on the basis of the PA's nonlinear characteristics. We devise a novel method for modeling the PA amplifying dual-band signals. The method makes it possible to model it merely by performing a one-tone test, making use of the Volterra series expansion and the general Wiener model. We then use the Mehler formula to derive the closed-form expressions of the PA's output power spectral density (PSD), ACPR, and EVM. The derivations are based on the assumption that the transmitted signals are complex Gaussian distributed in orthogonal frequency division multiplexing (OFDM) transmission systems. We validate the method by comparing measurement and simulation results and confirm it can appropriately predict the ACPR and EVM performance of the nonlinear PA output with OFDM inputs. In short, the method enables correct modeling of a wideband PA that amplifies dual-band signals merely by conducting a one-tone test.

This paper describes a robust three-dimensional (3D) surface reconstruction method that can automatically eliminate shadowing errors. For modeling shadowing effect, a new shadowing compensation model based on the angle distribution of backscattered electrons is introduced. Further, it is modified with respect to some practical factors. Moreover, the proposed iterative shadowing compensation method, which performs commutatively between the compensation of image intensities and the modification of the corresponding 3D surface, can effectively provide both an accurate 3D surface and compensated shadowless images after convergence.

In terms of the transmission-line theory, a general synthesis of a new class of optimum Chebyshev-type ultra-wideband bandpass (UWB) filter prototype composed of multistage stepped-impedance resonators (SIRs) and two short-circuited shunt stubs positioned at input- and output- ports is presented. By the comparison of the real and theoretical transfer functions, the design/characteristic equations are obtained for the design of the proposed filter prototype rather than the traditional design tables. The explicit expressions of one-stage and two-stage filters are then derived and reported. Accordingly, bandpass filters with an arbitrary FBW (Fractional Bandwidth) and passband ripple can be easily designed by solving the design equations. As an example, a 10-degree Chebyshev distributed filter (two-stage filter) with an FBW of 110% is synthesized to meet FCC's outdoor mask. The synthesized circuit model are confirmed by a commercial circuit simulator and then optimized by an EM simulator, fabricated in microstrip line and characterized by the network analyzer. The good agreements between the measured and predicted frequency responses validate the effectiveness of newly proposed filter prototype and the corresponding synthesis technique. In addition, the designed filter exhibits good characteristics of comparatively low insertion loss, quite sharp skirt, very flat group delay and good stopband (especially in lower one) as well. It should be also highlighted that, compared with the conventional filters composed merely of parallel-coupled SIRs or shunt short-circuit-stubs, the new prototype can reduce the overall length of the filter by more than 3/4λg. Moreover, in terms of the presented design technique, the proposed filter prototype can be also used to easily realize the UWB filters with an FBW even greater than 110%.

Binary sequences with low autocorrelation have important applications in communication systems and cryptography. In this paper, the autocorrelation values of binary Whiteman generalized cyclotomic sequences of order six and period pq are discussed. Our result shows that the autocorrelation of these sequences is four-valued and that the corresponding values are in {-1,3,-5,pq} if the parameters are chosen carefully.

This paper presents a Complex-Valued Neural Network-based sound localization method. The proposed approach uses two microphones to localize sound sources in the whole horizontal plane. The method uses time delay and amplitude difference to generate a set of features which are then classified by a Complex-Valued Multi-Layer Perceptron. The advantage of using complex values is that the amplitude information can naturally masks the phase information. The proposed method is analyzed experimentally with regard to the spectral characteristics of the target sounds and its tolerance to noise. The obtained results emphasize and confirm the advantages of using Complex-Valued Neural Networks for the sound localization problem in comparison to the traditional Real-Valued Neural Network model.

A compact DC-DC convertor is proposed and fabricated by LTCC technology. Multilayer packaging structure is utilized for size reduction. Measured results are provided to show good performance and validate proposed structure. With the inductor embedded into ferrite substrate, the convertor exhibits advantages of both miniature size and high reliability compared with conventional ones.