In this paper, a novel White-RGB (WRGB) color filter array-based imaging system for cell phone is presented to reduce noise and reproduce color in low illumination. The core process is based on adaptive diagonal color separation to recover color components from a white signal using diagonal reference blocks and location-based color ratio estimation in the luminance space. The experiments, which are compared with the RGB and state-of-the-art WRGB approaches, show that our imaging system performs well for various spatial frequency images and color restoration in low-light environments.

Software programs often include many defects that are not easy to detect because of the developers' mistakes, misunderstandings caused by the inadequate definition of requirements, and the complexity of the implementation. Due to the different skill levels of the testers, the significant increase in testing person-hours interferes with the progress of development projects. Therefore, it is desireable for any inexperienced developer to identify the cause of the defects. Model checking has been favored as a technique to improve the reliability earlier in the software development process. In this paper, we propose a verification method in which a Java source code control sequence is converted into finite automata in order to detect the cause of defects by using the model-checking tool UPPAAL, which has an exhaustive checking mechanism. We also propose a tool implemented by an Eclipse plug-in to assist general developers who have little knowledge of the model-checking tool. Because source code is generally complicated and large, the tool provides a step-wise verification mechanism based on the functional structure of the code and makes it easy to verify the business rules in the specification documents by adding a user-defined specification-based model to the source code model.

The Euler number of a binary image is an important topological property for pattern recognition, and can be calculated by counting certain bit-quads in the image. This paper proposes an efficient strategy for improving the bit-quad-based Euler number computing algorithm. By use of the information obtained when processing the previous bit quad, the number of times that pixels must be checked in processing a bit quad decreases from 4 to 2. Experiments demonstrate that an algorithm with our strategy significantly outperforms conventional Euler number computing algorithms.

In this letter, we evaluate the parasitic capacitance of an LCD touch panel, the description and implementation of a differential input sensing circuit, and an algorithm suitable for large LCDs with integrated touch function. When projected capacitive touch sensors are integrated with a liquid crystal display, the sensors have a very large amount of parasitic capacitance with the display elements. A differential input sensing circuit can detect small changes in the mutual capacitance from the touch of a finger. The circuit is realized using discrete components, and for the evaluation of a large-sized LCD touch panel, a printed circuit board touch panel is used.

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.

Recently, the wavelet-based estimation method has gradually been becoming popular as a new tool for software reliability assessment. The wavelet transform possesses both spatial and temporal resolution which makes the wavelet-based estimation method powerful in extracting necessary information from observed software fault data, in global and local points of view at the same time. This enables us to estimate the software reliability measures in higher accuracy. However, in the existing works, only the point estimation of the wavelet-based approach was focused, where the underlying stochastic process to describe the software-fault detection phenomena was modeled by a non-homogeneous Poisson process. In this paper, we propose an interval estimation method for the wavelet-based approach, aiming at taking account of uncertainty which was left out of consideration in point estimation. More specifically, we employ the simulation-based bootstrap method, and derive the confidence intervals of software reliability measures such as the software intensity function and the expected cumulative number of software faults. To this end, we extend the well-known thinning algorithm for the purpose of generating multiple sample data from one set of software-fault count data. The results of numerical analysis with real software fault data make it clear that, our proposal is a decision support method which enables the practitioners to do flexible decision making in software development project management.

The authors have evaluated a method of expanding the bit depth of image signals called SGRAD, which requires fewer calculations, while degrading the sharpness of images less. Where noise is superimposed on image signals, the conventional method for obtaining high bit depth sometimes incorrectly detects the contours of images, making it unable to sufficiently correct the gradation. Requiring many line memories is also an issue with the conventional method when applying the process to vertical gradation. As a solution to this particular issue, SGRAD improves the method of detecting contours with transiting gradation to effectively correct the gradation of image signals which noise is superimposed on. In addition, the use of a prediction algorithm for detecting gradation reduces the scale of the circuit with less correction of the vertical gradation.

A new scheme based on multi-order visual comparison is proposed for full-reference image quality assessment. Inspired by the observation that various image derivatives have great but different effects on visual perception, we perform respective comparison on different orders of image derivatives. To obtain an overall image quality score, we adaptively integrate the results of different comparisons via a perception-inspired strategy. Experimental results on public databases demonstrate that the proposed method is more competitive than some state-of-the-art methods, benchmarked against subjective assessment given by human beings.

Analysis of the trust network proves beneficial to the users in Online Social Networks (OSNs) for decision-making. Since the construction of trust propagation paths connecting unfamiliar users is the preceding work of trust inference, it is vital to find appropriate trust propagation paths. Most of existing trust network discovery algorithms apply the classical exhausted searching approaches with low efficiency and/or just take into account the factors relating to trust without regard to the role of distrust relationships. To solve the issues, we first analyze the trust discounting operators with structure balance theory and validate the distribution characteristics of balanced transitive triads. Then, Maximum Indirect Referral Belief Search (MIRBS) and Minimum Indirect Functional Uncertainty Search (MIFUS) strategies are proposed and followed by the Optimal Trust Inference Path Search (OTIPS) algorithms accordingly on the basis of the bidirectional versions of Dijkstra's algorithm. The comparative experiments of path search, trust inference and edge sign prediction are performed on the Epinions data set. The experimental results show that the proposed algorithm can find the trust inference path with better efficiency and the found paths have better applicability to trust inference.

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.

This paper proposes out-of-band emission reduction schemes for IEEE 802.11af based Wireless Local Area Network (WLAN) systems operating in TV White Spaces (TVWS). IEEE 802.11af adopts Orthogonal Frequency Division Multiplexing (OFDM) to exploit the TVWS spectrum effectively. The combination of the OFDM and TVWS may be able to solve the problem of frequency depletion. However the TVWS transmitter must satisfy a strict transmission spectrum mask and reduce out-of-band emission to protect the primary users. The digital convolution filter is one way of reducing the out-of-band emission. Unfortunately, implementing a strict mask needs a large number of filter taps, which causes high implementation complexity. Time-domain windowing is another effective approach. This scheme reduces out-of-band emission with low complexity but at the price of shortening the effective guard interval. This paper proposes a mechanism that jointly uses these two schemes for out-of-band emission reduction. Moreover, the appropriate windowing duration design is proposed in terms of both the out-of-band emission suppression and throughput performance for all mandatory mode of IEEE 802.11af system. The proposed time-domain windowing design reduces the number of multiplier by 96.5%.

Demand for wireless communication is increasing significantly, but the frequency resources available for wireless communication are quite limited. Currently, various countries are prompting the use of TV white spaces (TVWS). IEEE 802.11 Working Group (WG) has started a Task Group (TG), namely IEEE 802.11af, to develop an international standard for Wireless local Area Networks (WLANs) in TVWS. In order to increase maximum throughput, a channel aggregation mechanism is introduced in the draft standard. In Japan, ISDB-T based area-one-segment broadcasting system (Area-1seg) which is a digital TV broadcast service in limited areas has been permitted to offer actual TVWS services since April 2012. The operation of the IEEE 802.11af system shall not jeopardize the Area-1seg system due to the common operating frequency band. If the Area-1seg partially overlaps with the IEEE 802.11af in some frequency, the IEEE 802.11af cannot use the channel aggregation mechanism due to a lack of channels. As a result, the throughput of the IEEE 802.11af deteriorates. In this paper, the physical layer of IEEE 802.11af D4.0 is introduced briefly, and a partial subcarrier system for IEEE 802.11af is proposed to efficiently use the TVWS spectrum. The IEEE 802.11af co-exist with the Area-1seg by using null subcarriers. Computer simulation shows up to around 70% throughput gain is achieved with the proposed mechanism.

Proof-of-concept cyclic analog-to-digital converters (ADCs) have been designed and fabricated in 90-nm CMOS technology. The measurement results of an experimental prototype demonstrate the effectiveness of the proposed switched-capacitor (SC) architecture to realize a non-binary ADC based on β expansion. Different from the conventional binary ADC, a simple 1-bit/step structure for an SC multiplying digital-to-analog converter (MDAC) is proposed to present residue amplification by β (1 < β < 2). The redundancy of non-binary ADCs with radix β tolerates the non-linear conversion errors caused by the offsets of comparators, the mismatches of capacitors, and the finite DC gains of amplifiers, which are used in the MDAC. We also employed a radix value estimation algorithm to obtain an effective value of β for non-binary encoding; it can be realized by merely adding a simple conversion sequence and digital circuits. As a result, the power penalty of a high-gain wideband amplifier and the required accuracy of the circuit elements for a high-resolution ADC were largely relaxed so that the circuit design was greatly simplified. The implemented ADC achieves a measured peak signal-to-noise-and-distortion-ratio (SNDR) of 60.44dB, even with an op-amp with a poor DC gain (< 50dB) while dissipating 780µW in analog circuits at 1.4V and occupying an active area of 0.25 × 0.26mm2.

Participatory sensing is an emerging system that allows the increasing number of smartphone users to share effectively the minute statistical information collected by themselves. This system relies on participants' active contribution including intentional input data. However, a number of privacy concerns will hinder the spread of participatory sensing applications. It is difficult for resource-constrained mobile phones to rely on complicated encryption schemes. We should prepare a privacy-preserving participatory sensing scheme with low computation complexity. Moreover, an environment that can reassure participants and encourage their participation in participatory sensing is strongly required because the quality of the statistical data is dependent on the active contribution of general users. In this article, we present MNS-RRT algorithms, which is the combination of negative surveys and randomized response techniques, for preserving privacy in participatory sensing, with high levels of data integrity. By using our method, participatory sensing applications can deal with a data having two selections in a dimension. We evaluated how this scheme can preserve the privacy while ensuring data integrity.

This paper describes a new method for lossy audio signal compression via compressive sensing (CS). In this method, a structured shrinkage operator is employed to decompose the audio signal into three layers, with two sparse layers, tonal and transient, and additive noise, and then, both the tonal and transient layers are compressed using CS. Since the shrinkage operator is able to take into account the structure information of the coefficients in the transform domain, it is able to achieve a better sparse approximation of the audio signal than traditional methods do. In addition, we propose a sparsity allocation algorithm, which adjusts the sparsity between the two layers, thus improving the performance of CS. Experimental results demonstrated that the new method provided a better compression performance than conventional methods did.

In this letter, we present a new scheme to find small fundamental instantons (SFIs) of regular low-density parity-check (LDPC) codes for the linear programming (LP) decoding over the binary symmetric channel (BSC). Based on the fact that each instanton-induced graph (IIG) contains at least one short cycle, we determine potential instantons by constructing possible IIGs which contain short cycles and additional paths connected to the cycles. Then we identify actual instantons from potential ones under the LP decoding. Simulation results on some typical LDPC codes show that our scheme is effective, and more instantons can be obtained by the proposed scheme when compared with the existing instanton search method.

A high-speed and low-power 8-bit subranging analog-to-digital converter (ADC) based on 65-nm CMOS technology was fabricated. Rather than using digital foreground calibration, an analog-centric approach was adopted to reduce power dissipation. An offset cancelling charge-steering amplifier and capacitive-averaging technique effectively reduce the offset, noise, and power dissipation of the ADC. Moreover, the circuit used to compensate the kickback noise current from the comparator can also reduce the power dissipation. The reference-voltage generator for the fine ADC is composed of a fine ladder and a capacitor providing an AC signal path. This configuration reduces the power dissipation of the selection signal drivers for the analog multiplexer. A test chip fabricated using 65-nm digital CMOS technology achieved a high sampling rate of 1GHz, a low power dissipation of 17.5mW, and a figure of merit of 118fJ/conv.-step.

A new type of the affine projection (AP) algorithms which incorporates the sparsity condition of a system is presented. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weightings for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results show that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.

An LSI Chip-Package-Board integrated power noise simulation model and its validity is discussed in this paper. A unified power delivery network (PDN) of LSI chip, package, and printed circuit board (PCB) is connected with on-chip power supply current models with capacitor charging expression. The proposed modeling flow is demonstrated for the 32-bit microprocessor in a 1.0V 90nm CMOS technology. The PDN of the system that includes a chip, bonding wires and a printed circuit board is modeled in an equivalent circuit. The on-chip power supply noise monitoring technique and the magnetic probe method is applied for validating simulation results. Simulations and measurements explore power supply noise generation with the dependency on operating frequencies in the wide range from 10MHz to 300MHz, under the operation mode of dynamic frequency scaling, and in the long time operation with various operation codes. It is confirmed that the proposed power supply noise simulation model is helpful for the noise estimation throughout the design phase of the LSI system.

With the distributed data mining technique having been widely used in a variety of fields, the privacy preserving issue of sensitive data has attracted more and more attention in recent years. Our major concern over privacy preserving in distributed data mining is the accuracy of the data mining results while privacy preserving is ensured. Corresponding to the horizontally partitioned data, this paper presents a new hybrid algorithm for privacy preserving distributed data mining. The main idea of the algorithm is to combine the method of random orthogonal matrix transformation with the proposed secure multi-party protocol of matrix product to achieve zero loss of accuracy in most data mining implementations.