In this paper, we propose an algorithm for contrast enhancement based on Adaptive Histogram Equalization (AHE) to improve image quality. Most histogram-based contrast enhancement methods have problems with excessive or low image contrast enhancement. This results in unnatural output images and the loss of visual information. The proposed method manipulates the slope of the input of the Probability Density Function (PDF) histogram. We also propose a pixel redistribution method using convolution to compensate for excess pixels after the slope modification procedure. Our method adaptively enhances the contrast of the input image and shows good simulation results compared with conventional methods.

Toward the actualization of an automatic navigation system for fetoscopic tracheal occlusion (FETO) surgery, this paper proposes a 3D ultrasound (US) calibration-based approach that can locate the fetal facial surface, oral cavity, and airways by a registration between a 3D fetal model and 3D US images. The proposed approach consists of an offline process and online process. The offline process first reconstructs the 3D fetal model with the anatomies of the oral cavity and airways. Then, a point-based 3D US calibration system based on real-time 3D US images, an electromagnetic (EM) tracking device, and a novel cones' phantom, computes the matrix that transforms the 3D US image space into the world coordinate system. In the online process, by scanning the mother's body with a 3D US probe, 3D US images containing the fetus are obtained. The fetal facial surface extracted from the 3D US images is registered to the 3D fetal model using an ICP-based (iterative closest point) algorithm and the calibration matrices, so that the fetal facial surface as well as the oral cavity and airways are located. The results indicate that the 3D US calibration system achieves an FRE (fiducial registration error) of 1.49±0.44mm and a TRE (target registration error) of 1.81±0.56mm by using 24 fiducial points from two US volumes. A mean TRE of 1.55±0.46 mm is also achieved for measuring location accuracy of the 3D fetal facial surface extracted from 3D US images by 14 target markers, and mean location errors of 2.51±0.47 mm and 3.04±0.59 mm are achieved for indirectly measuring location accuracy of the pharynx and the entrance of the trachea, respectively, which satisfy the requirement of the FETO surgery.

Homotopy methods are known to be effective methods for finding DC operating points of nonlinear circuits with the theoretical guarantee of global convergence. There are several types of homotopy methods; as one of the most efficient methods for solving bipolar transistor circuits, the variable-gain homotopy (VGH) method is well-known. In this paper, we propose an efficient VGH method for solving bipolar and MOS transistor circuits. We also show that the proposed method converges to a stable operating point with high possibility from any initial point. The proposed method is not only globally convergent but also more efficient than the conventional VGH methods. Moreover, it can easily be implemented in SPICE.

Distance bounding protocols permit a verifier to compute the distance to a prover by measuring the execution time of n rounds of challenge-response authentication. Many protocols have been proposed to reduce the false acceptance rate of the challenge-response procedure. Until now, it has been widely believed that the lowest bound of the false acceptance rate is (1/2)n when n is the number of rounds and the prover can send only one response bit for each round. In this paper, we propose a new distance bounding protocol whose false acceptance rate is (1/3)n against the distance fraud attacks and the mafia fraud attacks. To reduce the false acceptance rate, we use two challenge bits for each iteration and introduce a way of expressing three cases with the use of only one response bit, the same bit length as existing protocols. Our protocol is the first distance bounding protocol whose false acceptance rate is lower than the currently believed minimal bound without increasing the number of response bits for each round.

Let p be an odd prime and m be any positive integer. Assume that n=2m and e is a positive divisor of m with m/e being odd. For the decimation factor $d=rac{(p^{m}+1)^2}{2(p^e+1)}$, the cross-correlation between the p-ary m-sequence ${tr_1^n(alpha^i)}$ and its decimated sequence ${tr_1^n(alpha^{di})}$ is investigated. The value distribution of the correlation function is completely determined. The results in this paper generalize the previous results given by Choi, Luo and Sun et al., where they considered some special cases of the decimation factor d with a restriction that m is odd. Note that the integer m in this paper can be even or odd. Thus, the decimation factor d here is more flexible than the previous ones. Moreover, our method for determining the value distribution of the correlation function is different from those adopted by Luo and Sun et al. in that we do not need to calculate the third power sum of the correlation function, which is usually difficult to handle.

In this paper, we investigate a combination scheme of subcarrier intensity-modulation (SIM) with spatial modulation (SM) for optical wireless communication. Using computer simulation, the performances of the proposed SIM/SM scheme are investigated and compared with those of the conventional SIM scheme in the additive white gaussian noise (AWGN) as well as in outdoor environment with turbulence induced fading characteristics. Numerical results show that the proposed SIM/SM scheme can outperform the conventional SIM in an environment with different spectral efficiencies. When the spectral efficiency is varied from 2bits/s/Hz to 4bits/s/Hz, an Eb/N0 gain of 2dB to 5dB is achieved, when the bit error rate of 10-5 is maintained. It shows that the employment of SM may further improve the power efficiency of SIM, when the number of subcarriers increases according to the spectral efficiency. When the spectral efficiency is 4bits/s/Hz, the SIM/SM scheme for 0.5 of log-irradiance variance in the log-normal turbulence channel shows the same performance as SIM with variance of 0.3. This means that the SIM/SM can be an alternative choice in even worse environments.

Flexural waves on a thin elastic plate are governed by the fourth-order differential equation, which is attractive not only from a harmonic analysis viewpoint but also useful for an efficient numerical method in the elastdynamics. In this paper, we proposed two novel ideas: (1) use of the tensor bases to describe flexural waves on inhomogeneous elastic plates, (2) weak form discretization to derive the second-order difference equation from the fourth-order differential equation. The discretization method proposed in this study is of preliminary consideration about the recursive transfer method (RTM) to analyse the scattering problem of flexural waves. More importantly, the proposed discretization method can be applied to any system which can be formulated by the weak form theory. The accuracy of the difference equation derived by the proposed discretization method is confirmed by comparing the analytical and numerical solutions of waveguide modes. As a typical problem to confirm the validity of the resultant governing equation, the influence of the spatially modulated elastic constant in waveguide modes is discussed.

Developers often face difficulties while using APIs. API usage patterns can aid them in using APIs efficiently, which are extracted from source code stored in software repositories. Previous approaches have mined repositories to extract API usage patterns by simply applying data mining techniques to the collection of method invocations of API objects. In these approaches, respective functional roles of invoked methods within API objects are ignored. The functional role represents what type of purpose each method actually achieves, and a method has a specific predefined order of invocation in accordance with its role. Therefore, the simple application of conventional mining techniques fails to produce API usage patterns that are helpful for code completion. This paper proposes an improved approach that extracts API usage patterns at a higher abstraction level rather than directly mining the actual method invocations. It embraces a multilevel sequential mining technique and uses categorization of method invocations based on their functional roles. We have implemented a mining tool and an extended Eclipse's code completion facility with extracted API usage patterns. Evaluation results of this tool show that our approach improves existing code completion.

This paper proposes a multipacket-per-slot reservation-based random access protocol with multiuser detection (MD) and automatic repeat request (ARQ), called MPRMD, and analyzes its performance by computer simulations. In MPRMD, before data packet (DP) transmission, a user terminal (UT) transmits a small access request packet (AP) that is composed of an orthogonal preamble sequence and a UT identifier (UT-ID) in a randomly selected minislot during a short dedicated period. Even when several APs collide, a base station (BS) distinguishes them by matched filtering against the preamble part and then extracts the UT-IDs after separating each AP by MD. If the APs are not successfully detected, a small number of minislots are additionally arranged to retransmit them. Thus, by using MD under AP crowded conditions, BS can maximally detect the access requests in a short period, which results in reducing the overhead. Furthermore, in the assignment of a slot, BS intentionally assigns one slot to multiple UTs in order to enhance the efficiency and separates UT's DPs by MD. Since MPRMD can detect a multitude of access requests by utilizing MD in the short period and efficiently assign the slot to separable DPs by MD, it can enhance the system throughput. Computer simulations are conducted to demonstrate the effectiveness of MPRMD. It is shown that the maximum throughputs of MPRMD with the average SNR of 30dB reach 1.4 and 1.7 packets/slot when a data packet is 10 times and 50 times as long as a control packet, respectively.

380keV proton irradiation effects are investigated on p-GaN and n-GaN layers in GaN-based light emitting diode (LED) by characterizing current-voltage (I-V) characteristics of p-n junction, and two-terminal resistance of p- and n-GaN on both type of layers in LED wafer. Two-terminal resistance on n-GaN kept its initial value after the 1×1014cm-2 fluence, and was remained the same order after the 1×1015cm-2 fluence. On the other hand, p-GaN showed sensitive increase in two-terminal resistance after the 1×1014cm-2, and six orders of increase after the 1×1015cm-2 fluence. Observed sensitive increase of resistivity in p-GaN is explained as a lower initial hole density in p-GaN than the initial electron density in n-GaN layer.

The success of any project can be affected by requirements changes. Requirements elicitation is a series of activities of adding, deleting, and modifying requirements. We refer to the completion of requirements elicitation of a software component as requirements maturation. When the requirements of each component have reached the 100% maturation point, no requirement will come to the component. This does not mean that a requirements analyst (RA) will reject the addition of requirements, but simply, that the additional requirements will not come to the project. Our motivation is to provide measurements by which an RA can estimate one of the maturation periods: the early, middle, or late period of the project. We will proceed by introducing the requirements maturation efficiency (RME). The RME of the requirements represents how quickly the requirements of a component reach 100% maturation. Then, we will estimate the requirements maturation period for every component by applying the RME. We assume that the RME is derived from its accessibility from an RA to the requirements source and the stability of the requirements. We model accessibility as the number of information flows from the source of the requirements to the RA, and further, model stability with the requirements maturation index (RMI). According to the multiple regression analysis of a case, we are able to get an equation on RME derived from these two factors with a significant level of 5%. We evaluated the result by comparing it to another case, and then discuss the effectiveness of the measurements.

To improve metal oxide semiconductor field effect transistors (MOSFET) performance, flat interface between gate insulator and silicon (Si) should be realized. In this paper, the influence of Si surface roughness on electrical characteristics of MOSFET with hafnium oxynitride (HfON) gate insulator formed by electron cyclotron resonance (ECR) plasma sputtering was investigated for the first time. The surface roughness of Si substrate was reduced by Ar/4.9%H2 annealing utilizing conventional rapid thermal annealing (RTA) system. The obtained root-mean-square (RMS) roughness was 0.07nm (without annealed: 0.18nm). The HfON was formed by 2nm-thick HfN deposition followed by the Ar/O2 plasma oxidation. The electrical properties of HfON gate insulator were improved by reducing Si surface roughness. It was found that the current drivability of fabricated nMOSFETs was remarkably increased by reducing Si surface roughness. Furthermore, the reduction of Si surface roughness also leads to decrease of the 1/f noise.

This paper describes a method for the efficient computation of the total autocorrelation for large multiple-output Boolean functions over a Shared Binary Decision Diagram (SBDD). The existing methods for computing the total autocorrelation over decision diagrams are restricted to single output functions and in the case of multiple-output functions require repeating the procedure k times where k is the number of outputs. The proposed method permits to perform the computation in a single traversal of SBDD. In that order, compared to standard BDD packages, we modified the way of traversing sub-diagrams in SBDD and introduced an additional memory function kept in the hash table for storing results of the computation of the autocorrelation between two subdiagrams in the SBDD. Due to that, the total amount of computations is reduced which makes the method feasible in practical applications. Experimental results over standard benchmarks confirm the efficiency of the method.

In this paper, the diversity multiplexing tradeoff (DMT) analysis of the non-coherent block-fading multiple antenna channel which uses a training-based channel estimation scheme at asymptotically high signal-to-noise ratios (SNRs) is extended to finite SNRs. This extension is performed for a single input multiple output (SIMO) maximal ratio combining (MRC) scheme. This analysis at finite SNRs is more useful because in practice, the training schemes operate at finite SNRs and their impact on DMT is more relevant at such SNRs. We show the non-applicability of the asymptotically high SNR relation, given by Zheng, to finite SNRs. We also show the equivalence of two existing training-based channel estimation schemes for any SIMO system, and using one of these, we compute the achievable finite-SNR DMT of the non-coherent SIMO-MRC scheme for two modes of the training scheme. We analyze the achievable finite-SNR DMT for different durations of training, modes of the training scheme, and SNRs. We show that the impact of the mode of the training scheme on finite-SNR DMT decreases as SNR increases. We also show that at asymptotically high SNRs, the achievable DMT in both modes of the SIMO-MRC scheme is equal to that of the non-coherent SIMO channel, as derived by Zheng.

We proposes a new adaptive spectral masking method of algebraic vector quantization (AVQ) for non-sparse signals in the modified discreet cosine transform (MDCT) domain. This paper also proposes switching the adaptive spectral masking on and off depending on whether or not the target signal is non-sparse. The switching decision is based on the results of MDCT-domain sparseness analysis. When the target signal is categorized as non-sparse, the masking level of the target MDCT coefficients is adaptively controlled using spectral envelope information. The performance of the proposed method, as a part of ITU-T G.711.1 Annex D, is evaluated in comparison with conventional AVQ. Subjective listening test results showed that the proposed method improves sound quality by more than 0.1 points on a five-point scale on average for speech, music, and mixed content, which indicates significant improvement.

This paper introduces an ontology-based method for checking requirements specification. Requirements ontology is a knowledge structure that contains functional requirements (FR), attributes of FR and relations among FR. Requirements specification is compared with functional nodes in the requirements ontology, then rules are used to find errors in requirements. On the basis of the results, requirements team can ask questions to customers and correctly and efficiently revise requirements. To support this method, an ontology-based checking tool for verification of requirements has been developed. Finally, the requirements checking method is evaluated through an experiment.

With the development of global navigation satellite systems (GNSS), the interference among global navigation satellite systems, known as the radio frequency compatibility problem, has become a matter of great concern to system providers and user communities. The acceptable compatibility threshold should be determined in the radio frequency compatibility assessment process. However, there is no common standard for the acceptable threshold in the radio frequency compatibility assessment. This paper firstly introduces the comprehensive radio frequency compatibility methodology combining the spectral separation coefficient (SSC) and code tracking spectral sensitivity coefficient (CT_SSC). Then, a method for determination of the acceptable compatibility threshold is proposed. The proposed method considers the receiver processing phase including acquisition, code and carrier tracking and data demodulation. Simulations accounting for the interference effects are carried out at each time step and every place on earth. The simulations mainly consider the signals of GPS, Galileo and BeiDou Navigation Satellite System (BDS) in the L1 band. Results show that all of the sole systems are compatible with other GNSS systems with respect to a special receiver configuration used in the simulations.

The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.

This paper presents a novel liver segmentation algorithm that achieves higher performance than conventional algorithms in the segmentation of cases with unusual liver shapes and/or large liver lesions. An L1 norm was introduced to the mean squared difference to find the most relevant cases with an input case from a training dataset. A patient-specific probabilistic atlas was generated from the retrieved cases to compensate for livers with unusual shapes, which accounts for liver shape more specifically than a conventional probabilistic atlas that is averaged over a number of training cases. To make the above process robust against large pathological lesions, we incorporated a novel term based on a set of “lesion bases” proposed in this study that account for the differences from normal liver parenchyma. Subsequently, the patient-specific probabilistic atlas was forwarded to a graph-cuts-based fine segmentation step, in which a penalty function was computed from the probabilistic atlas. A leave-one-out test using clinical abdominal CT volumes was conducted to validate the performance, and proved that the proposed segmentation algorithm with the proposed patient-specific atlas reinforced by the lesion bases outperformed the conventional algorithm with a statistically significant difference.

In this Letter, a new face recognition approach based on curvelets and local ternary patterns (LTP) is proposed. First, we observe that the curvelet transform is a new anisotropic multi-resolution transform and can efficiently represent edge discontinuities in face images, and that the LTP operator is one of the best texture descriptors in terms of characterizing face image details. This motivated us to decompose the image using the curvelet transform, and extract the features in different frequency bands. As revealed by curvelet transform properties, the highest frequency band information represents the noisy information, so we directly drop it from feature selection. The lowest frequency band mainly contains coarse image information, and thus we deal with it more precisely to extract features as the face's details using LTP. The remaining frequency bands mainly represent edge information, and we normalize them for achieving explicit structure information. Then, all the extracted features are put together as the elementary feature set. With these features, we can reduce the features' dimension using PCA, and then use the sparse sensing technique for face recognition. Experiments on the Yale database, the extended Yale B database, and the CMU PIE database show the effectiveness of the proposed methods.