In this paper, with a modification of our earlier construction in [12], new classes of optimal LHZ FHS sets with new parameters are obtained which are optimal in the sense that their parameters meet the Peng-Fan-Lee bound. It is shown that all the sequences in the proposed FHS sets are shift distinct. The proposed FHS sets are suitable for quasi-synchronous time/frequency hopping code division multiple access systems to eliminate multiple-access interference.

We consider single and multiple attacker scenarios in guessing and obtain bounds on various success parameters in terms of Renyi entropies. We also obtain a new derivation of the union bound.

To achieve more high speed and high quality systems of wireless communications, orthogonal frequency division multiple access (OFDMA) has been proposed. Moreover, OFDMA considering the multiuser diversity (MUDiv) has been also proposed to achieve more high system performance. On the other hand, the conventional MUDiv/OFDMA requires large complexity to select the subcarrier of each user. To solve this problem, we have proposed a MUDiv/OFDMA based on the low granularity block (LGB). However, it degrades the system performance in the environment which contains many deep faded subcarrier channels. Therefore, in this paper, we propose a cooperative LGB-MUDiv/OFDMA to mitigate the influence due to the deep faded subcarrier channel.

As VLSI process node continue to shrink, chemical mechanical planarization (CMP) process for copper interconnect has become an essential technique for enabling many-layer interconnection. Recently, Edge-over-Erosion error (EoE-error), which originates from overpolishing and could cause yield loss, is observed in various CMP processes, while its mechanism is still unclear. To predict these errors, we propose an EoE-error prediction method that exploits machine learning algorithms. The proposed method consists of (1) error analysis stage, (2) layout parameter extraction stage, (3) model construction stage and (4) prediction stage. In the error analysis and parameter extraction stages, we analyze test chips and identify layout parameters which have an impact on EoE phenomenon. In the model construction stage, we construct a prediction model using the proposed multi-level machine learning method, and do predictions for designed layouts in the prediction stage. Experimental results show that the proposed method attained 2.7∼19.2% accuracy improvement of EoE-error prediction and 0.8∼10.1% improvement of non-EoE-error prediction compared with general machine learning methods. The proposed method makes it possible to prevent unexpected yield loss by recognizing EoE-errors before manufacturing.

The energy consumption of the Internet has a huge impact on the world economy and it is likely to increase every year. In present backbone networks, pairs of nodes are connected by “bundles” of multiple physical cables that form one logical link and energy saving can be achieved by shutting down unused network resources. The hose model can support traffic demand variations among node pairs in different time periods because it accommodates multiple traffic matrices unlike the pipe model which supports only one traffic matrix. This paper proposes an OSPF (Open Shortest Path First) link weight optimization scheme to reduce the network resources used for the hose model considering single link failures. The proposed scheme employs a heuristic algorithm based on simulated annealing to determine a suitable set of link weights to reduce the worst-case total network resources used, and considering any single link failure preemptively. It efficiently selects the worst-case performance link-failure topology and searches for a link weight set that reduces the worst-case total network resources used. Numerical results show that the proposed scheme is more effective in the reduction of worst-case total network resources used than the conventional schemes, Start-time Optimization and minimum hop routing.

Industrial applications such as automotive ones require a cheap communication mechanism to send out communication messages from node to node by their deadline time. This paper presents a design paradigm in which we optimize both assignment of a network node to a bus and slot multiplexing of a FlexRay network system under hard real-time constraints so that we can minimize the cost of wire harness for the FlexRay network system. We present a cost minimization problem as a non-linear model. We developed a network synthesis tool which was based on simulated annealing. Our experimental results show that our design paradigm achieved a 50.0% less cost than a previously proposed approach for a virtual cost model.

In the impulse noise removal from a color image, vector filters are suitable for suppressing false color generation. However, the vector filters do not select optimal vectors to restore noise corrupted pixels. To cope with this problem, a cost function-based vector filter is proposed in this letter.

A method to synthesize facial caricatures with non-planar expression is proposed. Several methods have been already proposed to synthesize facial caricatures automatically, but they mainly synthesize plane facial caricatures which look somewhat monotonous. In order to generate expressive facial caricature, the image should be expressed in non-planar style, expressing the depth of the face by shading and highlighting. In this paper, a new method to express such non-planar effect in facial caricatures is proposed by blending the grayscale information of the real face image into the plane caricature. Some methods also have been proposed to generate non-planar facial caricature, but the proposed method can adjust the degree of non-planar expression by interactive evolutionary computing, so that the obtained expression is satisfied by the user based on his/her subjective criteria. Since the color of the face looks changed, when the grayscale information of the natural face image is mixed, the color information of the skin area are also set by interactive evolutionary computing. Experimental results show the high performance of the proposed method.

Joint signal detection and channel estimation based on the expectation-maximization (EM) algorithm has been investigated for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) mobile communications over fast-fading channels. The previous work in [20] developed a channel estimation method suitable for the EM-based iterative receiver. However, it remained possible for unreliable received signals to be repetitively used during the iterative process. In order to improve the EM-based iterative receiver further, this paper proposes spatial removal from the perspective of a message-passing algorithm on factor graphs. The spatial removal performs the channel estimation of a targeted antenna by using detected signals that are obtained from the received signals of all antennas other than the targeted antenna. It can avoid the repetitive use of unreliable received signals for consecutive signal detection and channel estimation. Appropriate applications of the spatial removal are also discussed to exploit both the removal effect and the spatial diversity. Computer simulations under fast-fading conditions demonstrate that the appropriate applications of the spatial removal can improve the packet error rate (PER) of the EM-based receiver thanks to both the removal effect and the spatial diversity.

In recent years, Ethernet fabrics have been developed with a view to using resources efficiently and simplifying the operation of data center networks. With Ethernet fabrics, frames are forwarded along the shortest paths based on routing tables without blocking ports. Ethernet fabrics are expected to be employed in more general networks including carrier access networks. In particular, the use of shortest path bridging MAC (SPBM) is expected to allow smooth migration from existing networks. With SPBM, networks can be flexibly constructed on demand in any network topology. If an arbitrary topology is constructed, traffic paths can overlap on specific links and throughput unfairness occurs. However, it is difficult to achieve accurate weighted fairness with existing schemes. This paper proposes employing weighted N rate N+1 color marking (WNRN+1CM) in SPBM networks to achieve per-flow weighted fairness. WNRN+1CM was developed to realize weighted fairness in layer-2 ring networks and the applicability to other network topologies has not yet been discussed. The outline of WNRN+1CM in SPBM is as follows. The weight and the maximum rate are provided for each flow at edge bridges. When edge bridges receive frames from outside the SPBM domain, they assign colors to frames according to the input rate and the weight of each flow. The color indicates the dropping priority. If the input rate exceeds the maximum rate, frames are discarded to limit the throughput. Core bridges selectively discard frames based on their color and the dropping threshold when congestion occurs. The bandwidth is allocated based on the weights. The performance of WNRN+1CM is evaluated with a theoretical analysis and computer simulations. WNRN+1CM can achieve weighted fairness in aggregation networks and multipoint networks. The throughput ratio matches the weights and the flow throughputs are limited to their maximum rate regardless of changes in traffic.

An efficient subcarrier allocation scheme of a supporting cell is proposed to recover the communication of faulty cell users in an OFDM-based wireless system. With the proposed subcarrier allocation scheme, the number of subcarriers allocated to faulty cell users is maximized while the average throughput of supporting cell users is maintained at a desired level. To find the maximum number of subcarriers allocated to faulty cell users, the average throughput of the subcarrier with the k-th smallest channel gain in a subcarrier group is derived by an inductive method. It is shown by simulation that the proposed subcarrier allocation scheme can provide more subcarriers to faulty cell users than the random selection subcarrier allocation scheme.

As the development of Internet-of-Things is moving towards large scale industry, such as logistic and manifacturing, there is a need for end-users to get involved in the process of creating IoT easily. In this paper, we introduce PaperIO, a paper-based 3D I/O interface, in which a single piece of paper can be sensed and actuated at the same time in three dimensions using the technology of selective inductive power transmission. With this technology, paper material with multiple embedded receivers, can not only selectively receive inductive power to perform paper-computing behavior, but also work as input sensors to communicate with power transmitter wirelessly. This technology allows the creation of paper-based sensor and actuators, and forms an Interent of Embedded Paper-craft. This paper presents the detailed implementation of the system, results of the technical experiments, and a few sample applications of the presented paper-based 3D I/O interface, and finally discusses the future plan of this research.

Realization of a planar dual-band fork three-way power divider (PDBF3PD) with Cheng's equivalent structure is discussed. The Cheng's structure consists of two open-circuited stubs and a transmission line, and the characteristic impedances tend to be high. As a result, the realizable range of frequency ratios of upper frequency to lower frequency is limited in a narrow area. In this paper, an impedance scale factor is proposed to transform characteristic impedances into a realizable range and to facilitate the design of PDBF3PDs. Theoretical considerations are verified using a simulator of ADS2008U and by an experiment.

In Still-to-Video (S2V) face recognition, only a few high resolution images are registered for each subject, while the probe is video clips of complex variations. As faces present distinct characteristics under different scenarios, recognition in the original space is obviously inefficient. Thus, in this paper, we propose a novel discriminant analysis method to learn separate mappings for different scenario patterns (still, video), and further pursue a common discriminant space based on these mappings. Concretely, by modeling each video as a manifold and each image as point data, we form the scenario-oriented mapping learning as a Point-Manifold Discriminant Analysis (PMDA) framework. The learning objective is formulated by incorporating the intra-class compactness and inter-class separability for good discrimination. Experiments on the COX-S2V dataset demonstrate the effectiveness of the proposed method.

With IC design entering the nanometer scale integration, the reliability of VLSI has declined due to small-delay defects, which are hard to detect by traditional delay fault testing. To detect small-delay defects, on-chip delay measurement, which measures the delay time of paths in the circuit under test (CUT), was proposed. However, our pre-simulation results show that when using on-chip delay measurement method to detect small-delay defects, test generation under the single-path sensitization is required. This constraint makes the fault coverage very low. To improve fault coverage, this paper introduces techniques which use segmented scan and test point insertion (TPI). Evaluation results indicate that we can get an acceptable fault coverage, by combining these techniques for launch off shift (LOS) testing under the single-path sensitization condition. Specifically, fault coverage is improved 27.02∼47.74% with 6.33∼12.35% of hardware overhead.

Runtime analysis is to enhance the safety of critical systems by monitoring the change of corresponding external environments. In this paper, a modified FTA approach, making full utilization of the existing safety analysis result, is put forward to achieve runtime safety analysis. The procedures of the approach are given in detail. This approach could be widely used in safety engineering of critical systems.

In the theory of periodic gratings, there is no method to make up a numerical solution that satisfies the reciprocity so far. On the basis of the shadow theory, however, this paper proposes a new method to obtain a numerical solution that satisfies the reciprocity. The shadow thoery states that, by the reciprocity, the $m$th order scattering factor is an even function with respect to a symmetrical axis depending on the order $m$ of diffraction. However, a scattering factor obtained numerically becomes an even function only approximately, but not accurately. It can be decomposed to even and odd components, where an odd component represents an error with respect to the reciprocity and can be removed by the average filter. Using even components, a numerical solution that satisfies the reciprocity is obtained. Numerical examples are given for the diffraction of a transverse magnetic (TM) plane wave by a very rough periodic surface with perfect conductivity. It is then found that, by use of the average filter, the energy error is much reduced in some case.

This paper presents a spatial fading emulator for evaluating handset MIMO antennas in a cluster environment. The proposed emulator is based on Clarke's model and has the ability to control RF signals directly in spatial domain to generate an accurate radio propagation channel model, which includes both uniform and non-uniform angular power spectra (APS) in the horizontal plane. Characteristics of a propagation channel such as fading correlations, eigenvalues and MIMO channel capacities of handset antennas located in the vicinity of the emulator's ring can be evaluated. The measured results show that the fading emulator with 31 antenna probes is sufficient to evaluate fading correlation and MIMO channel capacity of handset antenna in the case of a narrow APS with the standard deviation of more than 20 degrees.

The applicability of at-speed scan-based logic built-in self-test (BIST) is being severely challenged by excessive capture power that may cause erroneous test responses even for good circuits. Different from conventional low-power BIST, this paper is the first to explicitly focus on achieving capture power safety with a novel and practical scheme, called capture-power-safe logic BIST (CPS-LBIST). The basic idea is to identify all possibly-erroneous test responses caused by excessive capture power and use the well-known approach of masking (bit-masking, slice-masking,vector-masking) to block them from reaching the multiple-input signature register(MISR). Experiments with large benchmark circuits and a large industrial circuit demonstrate that CPS-LBIST can achieve capture power safety with negligible impact on test quality and circuit overhead.

In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.