In this letter we present an imperceptible and robust watermarking algorithm that uses a cryptographic hash function in the authentication application of digital medical imaging. In the proposed scheme we combine discrete Fourier transform (DFT) and local image masking to detect the watermark after a geometrical distortion and improve its imperceptibility. The image quality is measured by metrics currently used in digital image processing, such as VSNR, SSIM and PSNR.

This paper gives an outline of key technologies necessary for science-based agriculture. In order to design future agriculture, present agriculture should be redesigned based on the context of smart agriculture that indicates the overall form of agriculture including a social system while the present precision agriculture shows a technical form of agriculture only. Wireless Sensor Network (WSN) and the various type of optical sensors are assumed to be a basic technology of smart agriculture which intends the harmony with the economic development and sustainable agro-ecosystem. In this paper, the current state and development for the optical sensing for environment and plant are introduced.

Several models of feed-forward complex-valued neural networks have been proposed, and those with split and polar-represented activation functions have been mainly studied. Neural networks with split activation functions are relatively easy to analyze, but complex-valued neural networks with polar-represented functions have many applications but are difficult to analyze. In previous research, Nitta proved the uniqueness theorem of complex-valued neural networks with split activation functions. Subsequently, he studied their critical points, which caused plateaus and local minima in their learning processes. Thus, the uniqueness theorem is closely related to the learning process. In the present work, we first define three types of reducibility for feed-forward complex-valued neural networks with polar-represented activation functions and prove that we can easily transform reducible complex-valued neural networks into irreducible ones. We then prove the uniqueness theorem of complex-valued neural networks with polar-represented activation functions.

Segmenting foreground objects in unconstrained dynamic scenes still remains a difficult problem. We present a novel unsupervised segmentation approach that allows robust object segmentation of dynamic scenes with large displacements. To make this possible, we project motion based foreground region hypotheses generated via standard optical flow onto visual saliency regions. The motion hypotheses correspond to inside seeds mapping of the motion boundary. For visual saliency, we generalize the image signature method from images to videos to delineate saliency mapping of object proposals. The mapping of image signatures estimated in Discrete Cosine Transform (DCT) domain favor stand-out regions in the human visual system. We leverage a Markov random field built on superpixels to impose both spatial and temporal consistence constraints on the motion-saliency combined segments. Projecting salient regions via an image signature with inside mapping seeds facilitates segmenting ambiguous objects from unconstrained dynamic scenes in presence of large displacements. We demonstrate the performance on fourteen challenging unconstrained dynamic scenes, compare our method with two state-of-the-art unsupervised video segmentation algorithms, and provide quantitative and qualitative performance comparisons.

We investigate non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) in the cellular multiple-input multiple-output (MIMO) downlink for systems beyond LTE-Advanced. Taking into account the overhead for the downlink reference signaling for channel estimation at the user terminal in the case of non-orthogonal multiuser multiplexing and the applicability of the SIC receiver in the MIMO downlink, we propose intra-beam superposition coding of a multiuser signal at the transmitter and the spatial filtering of inter-beam interference followed by the intra-beam SIC at the user terminal receiver. The intra-beam SIC cancels out the inter-user interference within a beam. Regarding the transmitter beamforming (precoding), in general, any kind of beamforming matrix determination criteria can be applied to the proposed NOMA method. In the paper, we assume open loop-type random beamforming, which is very efficient in terms of the amount of feedback information from the user terminal. Furthermore, we employ a weighted proportional fair (PF)-based resource (beam of each frequency block and power) allocation for the proposed method. Simulation results show that the proposed NOMA method using the intra-beam superposition coding and SIC simultaneously achieves better sum and cell-edge user throughput compared to orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems.

In cognitive radar systems (CRSs), target scattering coefficients (TSC) can be utilized to improve the performance of target identification and classification. This work considers the problem of TSC estimation for temporally correlated target. Multiple receive antennas are adopted to receive the echo waveforms, which are interfered by the signal-dependent clutter. Unlike existing estimation methods in time domain, a novel estimation method based on Kalman filtering (KF) is proposed in frequency domain to exploit the temporal TSC correlation, and reduce the complexity of subsequent waveform optimization. Additionally, to minimize the mean square error of estimated TSC at each KF iteration, in contrary to existing works, we directly model the design process as an optimization problem, which is non-convex and cannot be solved efficiently. Therefore, we propose a novel method, similar in some way to semi-definite programming (SDP), to convert the non-convex problem into a convex one. Simulation results demonstrate that the estimation performance can be significantly improved by the KF estimation with optimized waveform.

A new algorithm for separating mass spectra into individual substances for explosives detection is proposed. In the field of mass spectrometry, separation methods, such as principal-component analysis (PCA) and independent-component analysis (ICA), are widely used. All components, however, have no negative values, and the orthogonality condition imposed on components also does not necessarily hold in the case of mass spectra. Because these methods allow negative values and PCA imposes an orthogonality condition, they are not suitable for separation of mass spectra. The proposed algorithm is based on probabilistic latent-component analysis (PLCA). PLCA is a statistical formulation of non-negative matrix factorization (NMF) using KL divergence. Because PLCA imposes the constraint of non-negativity but not orthogonality, the algorithm is effective for separating components of mass spectra. In addition, to estimate the components more accurately, a sparsity constraint is applied to PLCA for explosives detection. The main contribution is industrial application of the algorithm into an explosives-detection system. Results of an experimental evaluation of the algorithm with data obtained in a real railway station demonstrate that the proposed algorithm outperforms PCA and ICA. Also, results of calculation time demonstrate that the algorithm can work in real time.

We propose a novel sparse representation-based direction-of-arrival (DOA) estimation method. In contrast to those that approximate l0-norm minimization by l1-norm minimization, our method designs a reweighted l1 norm to substitute the l0 norm. The capability of the reweighted l1 norm to bridge the gap between the l0- and l1-norm minimization is then justified. In addition, an array covariance vector without redundancy is utilized to extend the aperture. It is proved that the degree of freedom is increased as such. The simulation results show that the proposed method performs much better than l1-type methods when the signal-to-noise ratio (SNR) is low and when the number of snapshots is small.

In indoor localization using sensor networks, performance improvements are required for non-line-of-sight (NLOS) environments in which the estimation error is high. NLOS mitigation schemes involve the detection and elimination of the NLOS measurements. The iterative minimum residual (IMR) scheme, which is often applied to the localization scheme using the time of arrival (TOA), is commonly employed for this purpose. The IMR scheme is a low-complexity scheme and its NLOS detection performance is relatively high. However, when there are many NLOS nodes in a sensor field, the NLOS detection error of the IMR scheme increases and the estimation accuracy deteriorates. Therefore, we propose a new scheme that exploits coarse NLOS detection based on stochastic characteristics prior to the application of the IMR scheme to improve the localization accuracy. Improved performances were confirmed in two NLOS channel models by performing numerical simulations.

To eliminate casting shadows of moving objects, which cause difficulties in vision applications, a novel method is proposed based on Visual background extractor by altering its updating mechanism using relevant spatiotemporal information. An adaptive threshold and a spatial adjustment are also employed. Experiments on typical surveillance scenes validate this scheme.

A K-user parallel concatenated code (PCC) is proposed for a Gaussian multiple-access channel with symbol synchronization, equal-power, and equal-rate users. In this code, each user employs a PCC with M+1 component codes, where the first component code is a rate-1/q repetition code and the other M component codes are the same rate-1 recursive convolutional (RC) codes. By designing the repetition coding rate and the RC component code, the K-user PCC achieve reliable transmission for a given number of users and noise level. Two decoding schemes are considered: low-density parity-check (LDPC)-like decoding and Turbo-like decoding. For each decoding scheme, a fixed point analysis is given to optimize the parameters: the rate of repetition component code 1/q, the number of RC component codes M, or the RC component codes themselves. The analysis shows that an accumulate code is the optimal RC component code for a K-user PCC, in the sense of achieving the maximum sum rate. The K-user PCC with an accumulate component code achieves a larger sum rate in the high rate region than the conventional scheme of an error correction code serially concatenated with spreading under similar encoding and decoding complexity.

Cu-Mo alloy carries forward not only high electrical conductivity and high thermal conductivity from Cu but also high hardness from Mo, which makes it a promising potential application in electrical contact fields. In this paper, arc characteristic and erosion characteristic of Cu-Mo contacts are studied with a bridge-type contact high speed break mechanism on DC270 V/200 A load condition. And in each experiment group, 2500 times break operations are carried out. During every break operation, a high-speed AD card is used to record voltage and current signal of the arc, a high-speed camera is applied to record arcing process, and the temperature of contacts and arc are acquired by thermocouple and spectrometer, respectively. The mass and contact resistance of contacts are measured before and after every group experiment. Besides, the photograph of contact surface is taken by SEM to help analyze the erosion characteristic. The comparison between Cu-Mo contacts and Cu contacts indicates that although Cu contacts have a better electrical conductivity and thermal conductivity, Cu-Mo contacts can decrease the temperature of arc to prevent thermal breakdown, and they are also harder to be ablated and have a longer life span.

In the log-likelihood ratio (LLR) domain, the belief propagation (BP) decoding algorithm for polar codes incurs high computation complexity due to the computation of the hyperbolic functions in the node update rules. In this paper, we propose a linear approximation method based on the principle of equal spacing to simplify the hyperbolic functions in the BP decoding algorithm. Our method replaces the computation of hyperbolic functions with addition and multiplication operations in the node update rules. Simulation results show that the performance of the modified BP decoding algorithm is almost the same as the original BP decoding algorithm in the low Signal to Noise Ratio (SNR) region, and in the high SNR region the performance of our method is slightly worse. The modified BP decoding algorithm is only implemented with addition and multiplication operations, which greatly reduces computation complexity, and simplifies hardware implementation.

User context and user location in particular play an important role in location-based services (LBS). The location can be determined by various positioning methods. These are typically evaluated with average positioning error or percentile values, which are not the most suitable metrics for evaluation of how a positioning method functions in the semantic space. Therefore, we propose a new method for evaluation of positioning accuracy in the semantic space. We focus on two types of semantic user locations that are widely available in urban areas: the street address and the categories of the surrounding points of interest (POIs). We demonstrate its use on ten different positioning methods: a standalone satellite navigation device, GPS module on a smartphone, two versions of Foursquare positioning service, Google positioning service, a positioning service of the local mobile operator, and four other possible variants of mobile operator-based positioning methods. The evaluation suggests that approach with the street addresses is more promising approach due to either sparse or unevenly distributed POIs. Furthermore, some of the positioning methods that are less accurate in Euclidean space, such as a combination of the GPS data with the mobile operator-based method that relies on the propagation models, performed comparably well in the semantic space as the methods that are using more accurate technologies, such as Google and Foursquare.

In this letter, a simple dispersion matrix design method for generalized space-time shift keying is presented, in which the dispersion matrices are systematically constructed with cyclic identity matrix, without the need of computer search. The proposed scheme is suitable for any number of transmit antennas greater than two, and can achieve the transmit diversity order of two except two special cases. Simulation results are presented to verify our theoretical analysis and the performance of the proposed scheme.

This paper presents a cell-based all-digital phase-locked loop (ADPLL) with hierarchical gated digitally controlled oscillator (G-DCO) for low voltage operation, wide frequency range as well as low-power consumption. In addition, a new time-domain hierarchical frequency estimation algorithm (HFEA) for frequency acquisition is proposed to estimate the output frequency in 1.5MF (MF = 3 in this paper) cycles and this fast lock-in time is suitable to the dynamic voltage frequency scaling (DVFS) systems. A hierarchical G-DCO is proposed to work at low supply voltage to reduce the power consumption and at the same time to achieve wide frequency range and precise frequency resolution. The core area of the proposed ADPLL is 0.02635 mm2. In near-threshold region (VDD = 0.36 V), the proposed ADPLL only dissipates 68.2 µW and has a rms period jitter of 1.25% UI at 60 MHz output clock frequency. Under 0.5 V VDD operation, the proposed ADPLL dissipates 404.2 µW at 400 MHz. The fast lock-in time of 4.489 µs and the low jitter performance below 0.5% UI at 400 MHz output clock frequency in the proposed ADPLL are suitable in event-driven or DVFS applications.

Recently ICT has been improved rapidly, and it is likely to make a contribution to effective disaster response. However, ICT is not utilized effectively in disaster response because the environment for ICT management is not considered enough. In this paper, we retrieve lessons learned from actual response at the past disasters in Japan, and introduce them following disaster response process model based on human psychological manner. In another point, we suggest significance of Common Operational Picture with spatial information following advanced case study in the United States of America, and identify two essential issues for effective information and technology management. One is information status, such as statics or dynamic information. The other one is five elements for ICT management in disaster response: Governance, Standard Operating Procedures, Technology, Training and Exercise and Use.

In wireless LANs, wireless clients are associated with one of access points (APs) to obtain network connectivity, and the AP performs network traffic relay between the wired infrastructure and wireless clients. If a client with a low transmission rate is associated with an AP, the throughput performance of all the clients that are associated with the AP is significantly degraded because of the long channel usage time of the low-rate client. Therefore, it is important to select an appropriate AP when a new client joins the wireless LAN to prevent the performance degradation. In this paper, we propose a traffic control that determines the feasible data traffic from an AP to the clients on the basis of the trade-off relationship between the equal-throughput and equal-airtime traffic allocation policies. We then propose a network-wide association algorithm that allows a client to be associated with the AP that can provide the highest throughput improvement. Simulation results indicate that the proposed algorithm achieves the better aggregate throughput and throughput fairness performances in IEEE 802.11 WLANs.

We demonstrated that load balancing using actual subscriber extension numbers was practical and effective against traffic congestion after a disaster based on actual data. We investigated the ratios of the same subscriber extension numbers in each prefecture and found that most of them were located almost evenly all over the country without being concentrated in a particular area. The ratio of every number except for the fourth-last digit in the last group of four numbers in a telephone number was used almost equally and located almost evenly all over the country. Tolerance against overload in the last, second-, and third-last single digits stays close to that in the ideal situation if we assume that each session initiation protocol server has a capacity in accordance with the ratio of each number on every single digit in the last group of four numbers in Japan. Although tolerance against overload in double-, triple-, and quadruple-digit numbers does not stay close to that in the ideal situation, it still remains sufficiently high in the case of double- and triple-digit numbers. Although tolerance against overload in the quadruple-digit numbers becomes low, disaster congestion is still not likely to occur in almost half of the area of Japan (23 out of 47 prefectures).

We propose a joint channel, power and rate allocation scheme to minimize the weighted group outage probability of the secondary users (SUs) in a downlink cognitive radio (CR) multicast network coexisting with a primary network, subject to the service outage constraint as well as the interference power constraint and the transmit power constraint. It is validated by simulation results that, compared to the existing schemes, the proposed scheme achieves lower group outage probability.