Many kinds of questionnaires, testing, and voting are performed in some completely electronic ways to do questions and answers on the Internet as Web applications, i.e. e-questionnaire systems, e-testing systems, and e-voting systems. Because there is no unified communication tool among the stakeholders of e-questionnaire, e-testing, and e-voting systems, until now, all the e-questionnaire, e-testing, and e-voting systems are designed, developed, used, and maintained in various ad hoc ways. As a result, the stakeholders are difficult to communicate to implement the systems, because there is neither an exhaustive requirement list to have a grasp of the overall e-questionnaire, e-testing, and e-voting systems nor a standardized terminology for these systems to avoid ambiguity. A general-purpose specification language to provide a unified description way for specifying various e-questionnaire, e-testing, and e-voting systems can solve the problems such that the stakeholders can refer to and use the complete requirements and standardized terminology for better communications, and can easily and unambiguously specify all the requirements of systems and services of e-questionnaire, e-testing, and e-voting, even can implement the systems. In this paper, we propose the first specification language, named “QSL,” with a standardized, consistent, and exhaustive list of requirements for specifying various e-questionnaire, e-testing, and e-voting systems such that the specifications can be used as the precondition of automatically generating e-questionnaire, e-testing, and e-voting systems. The paper presents our design addressing that QSL can specify all the requirements of various e-questionnaire, e-testing, and e-voting systems in a structured way, evaluates its effectiveness, performs real applications using QSL in case of e-questionnaire, e-testing, and e-voting systems, and shows various QSL applications for providing convenient QSL services to stakeholders.

In this paper, an improved charge pump (CP) and a modified nonlinear phase frequency detector (PFD) are designed and fabricated in a 90-nm CMOS process. The CP is optimized with a combination of circuit techniques such as pedestal error cancel scheme to eliminate the charge injection and the other non-ideal characteristics. The nonlinear PFD is based on a modified circuit topology to enhance the acquisition capability of the PLL. The optimized CP and nonlinear PFD are integrated into a Ka-band PLL. The measured output current mismatch ratio of the improved CP is less than 1% when the output voltage Vout fluctuates between 0.2 to 1.1V from a 1.2V power supply. The measured phase error detection range of the modified nonlinear PFD is between -2π and 2π. Owing to the modified CP and PFD, the measured reference spur of the Ka-band PLL frequency synthesizer containing the optimized CP and PFD is only -56.409dBc at 30-GHz at the locked state.

The capacity of optical transport networks has been increasing steadily and the networks are becoming more dynamic, complex, and transparent. Though it is common to use worst case assumptions for estimating the quality of transmission (QoT) in the physical layer, over provisioning results in high margin requirements. Accurate estimation on the QoT for to-be-established lightpaths is crucial for reducing provisioning margins. Machine learning (ML) is regarded as one of the most powerful methodological approaches to perform network data analysis and enable automated network self-configuration. In this paper, an artificial neural network (ANN) framework, a branch of ML, to estimate the optical signal-to-noise ratio (OSNR) of to-be-established lightpaths is proposed. It takes account of both nonlinear interference between spectrum neighboring channels and optical monitoring uncertainties. The link information vector of the lightpath is used as input and the OSNR of the lightpath is the target for output of the ANN. The nonlinear interference impact of the number of neighboring channels on the estimation accuracy is considered. Extensive simulation results show that the proposed OSNR estimation scheme can work with any RWA algorithm. High estimation accuracy of over 98% with estimation errors of less than 0.5dB can be achieved given enough training data. ANN model with R=4 neighboring channels should be used to achieve more accurate OSNR estimates. Based on the results, it is expected that the proposed ANN-based OSNR estimation for new lightpath provisioning can be a promising tool for margin reduction and low-cost operation of future optical transport networks.

This paper deals with the problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l2-scaling constraints for state-space digital filters. A novel measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure by jointly optimizing state-space realization and error feedback is explored, namely, the constrained optimization problem at hand is converted into an unconstrained problem and then the resultant problem is solved by employing a quasi-Newton algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.

Clinical researches show that the morbidity of coronary artery disease (CAD) is gradually increasing in many countries every year, and it causes hundreds of thousands of people all over the world dying for each year. As the optical coherence tomography with high resolution and better contrast applied to the lesion tissue investigation of human vessel, many more micro-structures of the vessel could be easily and clearly visible to doctors, which help to improve the CAD treatment effect. Manual qualitative analysis and classification of vessel lesion tissue are time-consuming to doctors because a single-time intravascular optical coherence (IVOCT) data set of a patient usually contains hundreds of in-vivo vessel images. To overcome this problem, we focus on the investigation of the superficial layer of the lesion region and propose a model based on local multi-layer region for vessel lesion components (lipid, fibrous and calcified plaque) features characterization and extraction. At the pre-processing stage, we applied two novel automatic methods to remove the catheter and guide-wire respectively. Based on the detected lumen boundary, the multi-layer model in the proximity lumen boundary region (PLBR) was built. In the multi-layer model, features extracted from the A-line sub-region (ALSR) of each layer was employed to characterize the type of the tissue existing in the ALSR. We used 7 human datasets containing total 490 OCT images to assess our tissue classification method. Validation was obtained by comparing the manual assessment with the automatic results derived by our method. The proposed automatic tissue classification method achieved an average accuracy of 89.53%, 93.81% and 91.78% for fibrous, calcified and lipid plaque respectively.

In conventional video streaming systems, various kind of video streams are delivered from a dedicated server (e.g., edge server) to the subscribers so that a video stream of higher quality level is encoded with a higher bitrate. In this paper, we consider the problem of delivering those video streams with the assistance of Peer-to-Peer (P2P) technology with as small server cost as possible while keeping the performance of video streaming in terms of the throughput and the latency. The basic idea of the proposed method is to divide a given video stream into several sub-streams called stripes as evenly as possible and to deliver those stripes to the subscribers through different tree-structured overlays. Such a stripe-based approach could average the load of peers, and could effectively resolve the overloading of the overlay for high quality video streams. The performance of the proposed method is evaluated numerically. The result of evaluations indicates that the proposed method significantly reduces the server cost necessary to guarantee a designated delivery hops, compared with a naive tree-based scheme.

We show that the non-trivial correlation of two properly chosen column sequences of length q-1 from the array structure of two Sidelnikov sequences of periods qe-1 and qd-1, respectively, is upper-bounded by $(2d-1)sqrt{q} + 1$, if $2leq e < d < rac{1}{2}(sqrt{q}-rac{2}{sqrt{q}}+1)$. Based on this, we propose a construction by combining properly chosen columns from arrays of size $(q-1) imes rac{q^e-1}{q-1}$ with e=2,3,...,d. The combining process enlarge the family size while maintaining the upper-bound of maximum non-trivial correlation. We also propose an algorithm for generating the sequence family based on Chinese remainder theorem. The proposed algorithm is more efficient than brute force approach.

Many quality metrics have been proposed for the compliance perception to assess haptic device performance and perceived results. Perceived compliance may be influenced by factors such as object properties, experimental conditions and human perceptual habits. In this paper, analysis of softness perception was conducted to find out relevant quality metrics dominating in the compliance perception system and their correlation with perception results, by expressing these metrics by basic physical parameters that characterizing these factors. Based on three psychophysical experiments, just noticeable differences (JNDs) for perceived softness of combination of different stiffness coefficients and damping levels rendered by haptic devices were analyzed. Interaction data during the interaction process were recorded and analyzed. Preliminary experimental results show that the discrimination ability of softness perception changes with the ratio of damping to stiffness when subjects exploring at their habitual speed. Analysis results indicate that quality metrics of Rate-hardness, Extended Rate-hardness and ratio of damping to stiffness have high correlation for perceived results. Further analysis results show that parameters that reflecting object properties (stiffness, damping), experimental conditions (force bandwidth) and human perceptual habits (initial speed, maximum force change rate) lead to the change of these quality metrics, which then bring different perceptual feeling and finally result in the change of discrimination ability. Findings in this paper may provide a better understanding of softness perception and useful guidance in improvement of haptic and teleoperation devices.

A monocone antenna is a type of monopole antenna with wideband characteristics. In this paper, a low-profile and small monocone antenna is proposed, by loading a circular plate and three oblique short elements. The characteristics of the proposed antenna are analyzed via simulation. Consequently, a low-profile and small monocone antenna can be obtained while maintaining the wideband characteristics. The relative bandwidth of the proposed antenna (voltage standing wave ratio (VSWR) ≤ 2) is greater than 158.9%. The frequency band of digital terrestrial television broadcasting and the mobile communication systems (from 470 to 3600MHz) in Japan can be completely covered with VSWR ≤ 2. In addition, the radiation patterns of the proposed antenna are omni-directional. The proposed antenna is prototyped, and the validity of the simulation is verified through measurement.

This paper proposes a deep neural network (DNN) based framework to address the problem of vector quantization (VQ) for high-dimensional data. The main challenge of applying DNN to VQ is how to reduce the binary coding error of the auto-encoder when the distribution of the coding units is far from binary. To address this problem, three fine-tuning methods have been adopted: 1) adding Gaussian noise to the input of the coding layer, 2) forcing the output of the coding layer to be binary, 3) adding a non-binary penalty term to the loss function. These fine-tuning methods have been extensively evaluated on quantizing speech magnitude spectra. The results demonstrated that each of the methods is useful for improving the coding performance. When implemented for quantizing 968-dimensional speech spectra using only 18-bit, the DNN-based VQ framework achieved an averaged PESQ of about 2.09, which is far beyond the capability of conventional VQ methods.

It is generally believed that jamming signals similar to communication signals tend to demonstrate better jamming effects. We believe that the above conclusion only works in certain situations. To select the correct jamming scheme for a multi-level quadrature amplitude modulation (MQAM) signal in a complex environment, an optimal jamming method based on orthogonal decomposition (OD) is proposed. The method solves the jamming problem from the perspective of the in-phase dimension and quadrature dimension and exhibits a better jamming effect than normal methods. The method can construct various unconventional jamming schemes to cope with a complex environment and verify the existing jamming schemes. The Experimental results demonstrate that when the jammer ideally knows the received power at the receiver, the proposed method will always have the optimal jamming effects, and the constructed unconventional jamming scheme has an excellent jamming effect compared with normal schemes in the case of a constellation distortion.

A program is non-interferent if it leaks no secret information to an observable output. However, non-interference is too strict in many practical cases and quantitative information flow (QIF) has been proposed and studied in depth. Originally, QIF is defined as the average of leakage amount of secret information over all executions of a program. However, a vulnerable program that has executions leaking the whole secret but has the small average leakage could be considered as secure. This counter-intuition raises a need for a new definition of information leakage of a particular run, i.e., dynamic leakage. As discussed in [5], entropy-based definitions do not work well for quantifying information leakage dynamically; Belief-based definition on the other hand is appropriate for deterministic programs, however, it is not appropriate for probabilistic ones.In this paper, we propose new simple notions of dynamic leakage based on entropy which are compatible with existing QIF definitions for deterministic programs, and yet reasonable for probabilistic programs in the sense of [5]. We also investigated the complexity of computing the proposed dynamic leakage for three classes of Boolean programs. We also implemented a tool for QIF calculation using model counting tools for Boolean formulae. Experimental results on popular benchmarks of QIF research show the flexibility of our framework. Finally, we discuss the improvement of performance and scalability of the proposed method as well as an extension to more general cases.

Constrained by quality-of-service (QoS), a robust transceiver design is proposed for multiple-input multiple-output (MIMO) interference channels with imperfect channel state information (CSI) under bounded error model. The QoS measurement is represented as the signal-to-interference-plus-noise ratio (SINR) for each user with single data stream. The problem is formulated as sum power minimization to reduce the total power consumption for energy efficiency. In a centralized manner, alternating optimization is performed at each node. For fixed transmitters, closed-form expression for the receive beamforming vectors is deduced. And for fixed receivers, the sum-power minimization problem is recast as a semi-definite program form with linear matrix inequalities constraints. Simulation results demonstrate the convergence and robustness of the proposed algorithm, which is important for practical applications in future wireless networks.

This letter proposes a novel dynamic channel assignment (DCA) scheme to improve the downlink system capacity in heterogeneous networks (HetNets) with fractional frequency reuse (FFR). In the proposed DCA scheme, the macro base station (MBS) finds small-cell base stations (SBSs) that give strong interference to macro user equipments (MUEs) and then dynamically assigns subchannels to the SBSs to serve their small-cell user equipments (SUEs) according to the cross-tier interference information to MUEs. Through simulation results, it is shown that the proposed DCA scheme outperforms other schemes in terms of the total system capacity.

In this letter, a polarization filtering based transmission (PFBT) scheme is proposed to enhance the spectrum efficiency in wireless communications. In such scheme, the information is divided into several parts and each is conveyed by a polarized signal with a unique polarization state (PS). Then, the polarized signals are added up and transmitted by the dual-polarized antenna. At the receiver side, the oblique projection polarization filters (OPPFs) are adopted to separate each polarized signal. Thus, they can be demodulated separately. We mainly focus on the construction methods of the OPPF matrix when the number of the separate parts is 2 and 3 and evaluate the performance in terms of the capacity and the bit error rate. In addition, we also discuss the probability of the signal separation when the number of the separate parts is equal or greater than 4. Theoretical results and simulation results demonstrate the performance of the proposed scheme.

In this paper, we consider a wide family of λ-quasi-twisted (λ-QT) codes of index 2 and provide a bound on the minimum Hamming distance. Moreover, we give a sufficient condition for dual containing with respect to Hermitian inner product of these involved codes. As an application, some good stabilizer quantum codes over small finite fields F2 or F3 are obtained from the class of λ-QT codes.

Deterioration of software quality developed by multiple organizations has become a serious problem. To predict software degradation after an organizational change, this paper investigates the influence of quality deterioration on software metrics by analyzing three software projects. To detect factors indicating a low evolvability, we focus on the relationships between the change in software metric values and refactoring tendencies. Refactoring after an organization change impacts the quality.

Existing fault localization based on neural networks utilize the information of whether a statement is executed or not executed to identify suspicious statements potentially responsible for a failure. However, the information just shows the binary execution states of a statement, and cannot show how important a statement is in executions. Consequently, it may degrade fault localization effectiveness. To address this issue, this paper proposes TFIDF-FL by using term frequency-inverse document frequency to identify a high or low degree of the influence of a statement in an execution. Our empirical results on 8 real-world programs show that TFIDF-FL significantly improves fault localization effectiveness.

In this paper, we consider the relationship between human preference and brain activity, especially pulse wave information using NIRS. First of all, we extracted the information of on pulse wave from the Hb changes signal of NIRS. By using the FFT to the Hb signals, we found out the 2-nd peak of power spectrum that is implying the frequency information of the pulse wave. The frequency deviation of 2-nd peak may have some information about the change of brain activity, it is associated with the human preference for viewing the significant image content.

We studied the detection of the incongruence between the two eyes' retinal images from occlusion perception. We previously analyzed the evasion action caused by occlusion by using green-red equiluminance, which is processed by parvocellular cells. Here we analyzed this action by using yellow-blue equiluminance, which is said to be treated by koniocellular cells and parvocellular cells. We observed that there were the cases in which the subject could perceive incongruence by the occlusion and other cases in which the subject could not perceive it. Significant differences were not seen in all conditions. Because a difference was seen in an evasion action at the time of the rim occlusion gaze when we compare the result for the yellow-blue equiluminance with the green-red equiluminance, it is suggested that the response for each equiluminance is different. We were able to clarify the characteristic difference between parvocellular cells and koniocellular cells from an occlusion experiment.