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.

We have improved a compact model for the injection-enhancedinsulated-gate bipolar transistor for inverter circuit simulation. The holeaccumulation of floating-base region and potential change are modeled. It turned out that negative capacitance which occurs by floating-base region has the dependence of frequency. It is necessary to consider the frequency dependence of the total gate capacitance for transient simulation. We analyzed the relationship between negative gate capacitance and current rise rate at the switch turn-on timing and device structure. The development model simulation result is well reproduced $I_{ extrm{c}}$ and $V_{ extrm{ce}}$ of measurement data, and the switching loss calculation accuracy is improved.

Underfill materials are used in a packaging of millimeter wave IC. However, there are few reports for dielectric properties of underfill materials in millimeter wave region. A cut-off circular waveguide method is one of a powerful technique to evaluate precisely complex permittivity in millimeter wave region. This method may be useful not only for low-loss materials, but also for mid-loss ones with loss tangent of 10$^{-2}$ order. In this paper, an evaluation technique based on the cut-off circular waveguide method is presented to measure mid-loss underfill materials. As a result, the relative permittivity $arepsilon_{r}$ and the loss tangent tan$delta$ are in the range of 2.8$sim $3.4 and (1.0$sim$1.6)$ imes10^{-2}$, respectively. Also, the measurement precision is 2.3% for $arepsilon_{r} approx 3$ and 40% for tan$delta approx 10^{-2}$.

We present a low-complexity complementary pair affine projection (CP-AP) adaptive filter which employs the intermittent update of the filter coefficients. To achieve both a fast convergence rate and a small residual error, we use a scheme combining fast and slow AP filters, while significantly reducing the computational complexity. By employing an evolutionary method which automatically determines the update intervals, the update frequencies of the two constituent filters are significantly decreased. Experimental results show that the proposed CP-AP adaptive filter has an advantage over conventional adaptive filters with a parallel structure in that it has a similar convergence performance with a substantial reduction in the total number of updates.

For an integer q≥2, new sets of q-phase aperiodic complementary sequences (ACSs) are constructed by using known sets of q-phase ACSs and certain matrices. Employing the Kronecker product to two known sets of q-phase ACSs, some sets of q-phase aperiodic complementary sequences with a new length are obtained. For an even integer q, some sets of q-phase ACSs with new parameters are generated, and their equivalent matrix representations are also presented.

In the traditional microphone array signal processing, the performance degrades rapidly when the array aperture decreases, which has been a barrier restricting its implementation in the small-scale acoustic system such as digital hearing aids. In this work a new compressed sampling method of miniature microphone array is proposed, which compresses information in the internal of ADC by means of mixture system of hardware circuit and software program in order to remove the redundancy of the different array element signals. The architecture of the method is developed using the Verilog language and has already been tested in the FPGA chip. Experiments of compressed sampling and reconstruction show the successful sparseness and reconstruction for speech sources. Owing to having avoided singularity problem of the correlation matrix of the miniature microphone array, when used in the direction of arrival (DOA) estimation in digital hearing aids, the proposed method has the advantage of higher resolution compared with the traditional GCC and MUSIC algorithms.

With the phenomenal explosion in online services, social networks are becoming an emerging ubiquitous platform for numerous services where service consumers require the selection of trustworthy service providers before invoking services with the help of other intermediate participants. Under this circumstance, evaluation of the trustworthiness of the service provider along the social trust paths from the service consumer to the service provider is required and to this end, selection of the optimal social trust path (OSTP) that can yield the most trustworthy evaluation result is a pre-requisite. OSTP selection with multiple quality of trust (QoT) constraints has been proven to be NP-Complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing solutions cannot guarantee the search efficiency, that is, they have difficulty in avoiding suboptimal solutions during the search process. Quantum annealing uses delocalization and tunneling to avoid local minima without sacrificing execution time. Several recent studies have proven that it is a promising way to tackle many optimization problems. In this paper, we propose a novel quantum annealing based OSTP selection algorithm (QA_OSTP) for large-scale complex social networks. Experiments show that QA_OSTP has better performance than its heuristic counterparts.

This paper gives a survey of intelligent computational techniques in medical and health care system. First, we briefly describe diagnosable techniques in medical image processing. Next, we demonstrate two ultrasonic surgery support systems for orthopedic and rectum cancer surgeons. In them, intelligent computational technique plays a primary role. Third, computational techniques are introduced in human health care system. Usually, this goal is not to apply clinical treatment but to home use to pay consciousness to health. In it, a simple ECG and respiration meter are introduced with a mat sheet which detects heart rate and respiration. Finally, a medical big data application is introduced, that is, body weight prediction is shown based on autoregressive model. Thus, we show that intelligent computing is effective and essential in modern medical and health care system.

Stochastic decoding provides ultra-low-complexity hardware for high-throughput parallel low-density parity-check (LDPC) decoders. Asynchronous stochastic decoding was proposed to demonstrate the possibility of low power dissipation and high throughput in stochastic decoders, but decoding might stop before convergence due to “lock-up”, causing error floors that also occur in synchronous stochastic decoding. In this paper, we introduce a wire-delay dependent (WDD) scheduling algorithm for asynchronous stochastic decoding in order to reduce the error floors. Instead of assigning the same delay to all computation nodes in the previous work, different computation delay is assigned to each computation node depending on its wire length. The variation of update timing increases switching activities to decrease the possibility of the “lock-up”, lowering the error floors. In addition, the WDD scheduling algorithm is simplified for the hardware implementation in order to eliminate time-averaging and multiplication functions used in the original WDD scheduling algorithm. BER performance using a regular (1024, 512) (3,6) LDPC code is simulated based on our timing model that has computation and wire delay estimated under ASPLA 90nm CMOS technology. It is demonstrated that the proposed asynchronous decoder achieves a 6.4-9.8× smaller latency than that of the synchronous decoder with a 0.25-0.3 dB coding gain.

Recently the word-based stream ciphers have been the subject of a considerable amount of research. The theory of such stream ciphers requires the study of the complexity of a multisequence. Let S1, S2, . . . , Sm be m N-ary sequences of period T, i.e., a multisequence. The relationship between the joint N-adic complexity and the number of the nonzero columns of the generalized Fourier transform for the N-ary multisequence is determined which generalizes the well-known result about the joint linear complexity and the generalized Fourier transform for a multisequence to the case of the joint N-adic complexity.

In this manuscript we present a methodology for reducing the impact of the hosting room reflections in sound field rendering applications based on loudspeaker arrays. The problem is formulated in a least-squares sense. Since matrices involved in the problem are ill-conditioned, it is important to devise a suitable technique for the regularisation of the pseudo-inverse. In this work we adopt a truncated SVD method. The truncation, in particular, aims at reducing the impact of numerical errors and also errors on the knowledge of the sound speed. We include a wide set of experimental results, which validate the proposed technique.

This paper presents a graph-based approach to designing arithmetic circuits over Galois fields (GFs) using normal basis representations. The proposed method is based on a graph-based circuit description called Galois-field Arithmetic Circuit Graph (GF-ACG). First, we extend GF-ACG representation to describe GFs defined by normal basis in addition to polynomial basis. We then apply the extended design method to Massey-Omura parallel multipliers which are well known as typical multipliers based on normal basis. We present the formal description of the multipliers in a hierarchical manner and show that the verification time can be greatly reduced in comparison with those of the conventional techniques. In addition, we design GF exponentiation circuits consisting of the Massey-Omura parallel multipliers and an inversion circuit over composite field GF(((22)2)2) in order to demonstrate the advantages of normal-basis circuits over polynomial-basis ones.

Millimeter-wave synthetic aperture imaging radiometer (SAIR) is a powerful sensor for near-field high-resolution observations. However, the large receiver number and system complexity affect the application of SAIR. To overcome this shortage (receiver number), an accurate imaging algorithm based on compressed sensing (CS) theory is proposed in this paper. For reconstructing the brightness temperature images accurately from the sparse SAIR with fewer receivers, the proposed CS-based imaging algorithm is used to accomplish the sparse reconstruction with fewer visibility samples. The reconstruction is performed by minimizing the $l_{1}$ norm of the transformed image. Compared to the FFT-based methods based on Fourier transform, the required receiver number can be further reduced by this method. The simulation results demonstrate that the proposed CS-based method has higher reconstruction accuracy for the sparse SAIR.

Visual quality evaluation is crucially important for various video and image processing systems. Traditionally, subjective image quality assessment (IQA) given by the judgments of people can be perfectly consistent with human visual system (HVS). However, subjective IQA metrics are cumbersome and easily affected by experimental environment. These problems further limits its applications of evaluating massive pictures. Therefore, objective IQA metrics are desired which can be incorporated into machines and automatically evaluate image quality. Effective objective IQA methods should predict accurate quality in accord with the subjective evaluation. Motivated by observations that HVS is highly adapted to extract irregularity information of textures in a scene, we introduce multifractal formalism into an image quality assessment scheme in this paper. Based on multifractal analysis, statistical complexity features of nature images are extracted robustly. Then a novel framework for image quality assessment is further proposed by quantifying the discrepancies between multifractal spectrums of images. A total of 982 images are used to validate the proposed algorithm, including five type of distortions: JPEG2000 compression, JPEG compression, white noise, Gaussian blur, and Fast Fading. Experimental results demonstrate that the proposed metric is highly effective for evaluating perceived image quality and it outperforms many state-of-the-art methods.

Reversible logic is becoming more and more popular due to the fact that many novel technologies such as quantum computing, low power CMOS circuit design or quantum optical computing are becoming more and more realistic. In quantum computing, reversible computing is the main venue for the realization and design of classical functions and circuits. We present a new approach to synthesis of reversible circuits using Kronecker Functional Lattice Diagrams (KFLD). Unlike many of contemporary algorithms for synthesis of reversible functions that use n×n Toffoli gates, our method synthesizes functions using 3×3 Toffoli gates, Feynman gates and NOT gates. This reduces the quantum cost of the designed circuit but adds additional ancilla bits. The resulting circuits are always regular in a 4-neighbor model and all connections are predictable. Consequently resulting circuits can be directly mapped in to a quantum device such as quantum FPGA [14]. This is a significant advantage of our method, as it allows us to design optimum circuits for a given quantum technology.

Let T1,T2,...,Tk be spanning trees in a graph G. If, for any two vertices u,v of G, the paths joining u and v on the k trees are mutually vertex-disjoint, then T1,T2,...,Tk are called completely independent spanning trees (CISTs for short) of G. The construction of CISTs can be applied in fault-tolerant broadcasting and secure message distribution on interconnection networks. Hasunuma (2001) first introduced the concept of CISTs and conjectured that there are k CISTs in any 2k-connected graph. Unfortunately, this conjecture was disproved by Péterfalvi recently. In this note, we give a necessary condition for k-connected k-regular graphs with ⌊k/2⌋ CISTs. Based on this condition, we provide more counterexamples for Hasunuma's conjecture. By contrast, we show that there are two CISTs in 4-regular chordal rings CR(N,d) with N=k(d-1)+j under the condition that k ≥ 4 is even and 0 ≤ j ≤ 4. In particular, the diameter of each constructed CIST is derived.

Despite the increasing use of mobile computing, exploiting its full potential is difficult due to its inherent characteristics such as error-prone transmission channels, diverse node capabilities, frequent disconnections and mobility. Mobile Cloud Computing (MCC) is a paradigm that is aimed at overcoming previous problems through integrating mobile devices with cloud computing. Mobile devices, in the traditional client-server architecture of MCC, offload their tasks to the cloud to utilize the computation and storage resources of data centers. However, along with the development of hardware and software technologies in mobile devices, researchers have begun to take into consideration local resource sharing among mobile devices themselves. This is defined as the cooperation based architecture of MCC. Analogous to the conventional terminology, the resource platforms that are comprised of surrounding surrogate mobile devices are called local resource clouds. Some researchers have recently verified the feasibility and benefits of this strategy. However, existing work has neglected an important issue with this approach, i.e., how to construct local resource clouds in dynamic mobile wireless networks. This paper presents the concept and design of a local resource cloud that is both energy and time efficient. Along with theoretical models and formal definitions of problems, an efficient heuristic algorithm with low computational complexity is also presented. The results from simulations demonstrate the effectiveness of the proposed models and method.

In this paper, we propose a novel approach for multiple-shot people re-identification. Due to high variance in camera view, light illumination, non-rigid deformation of posture and so on, there exists a crucial inter-/intra- variance issue, i.e., the same people may look considerably different, whereas different people may look extremely similar. This issue leads to an intractable, multimodal distribution of people appearance in feature space. To deal with such multimodal properties of data, we solve the re-identification problem under a local distance comparison framework, which significantly alleviates the difficulty induced by varying appearance of each individual. Furthermore, we build an energy-based loss function to measure the similarity between appearance instances, by calculating the distance between corresponding subsets in feature space. This loss function not only favors small distances that indicate high similarity between appearances of the same people, but also penalizes small distances or undesirable overlaps between subsets, which reflect high similarity between appearances of different people. In this way, effective people re-identification can be achieved in a robust manner against the inter-/intra- variance issue. The performance of our approach has been evaluated by applying it to the public benchmark datasets ETHZ and CAVIAR4REID. Experimental results show significant improvements over previous reports.

Shadow mapping is an efficient method to generate shadows in real time computer graphics and has broad variations from hard to soft shadow synthesis. Soft shadowing based on shadow mapping is a blurring technique on a shadow map or on screen space. Blurring on screen space has an advantage for efficient sampling on a shadow map, since the blurred target array has exactly the same coordinates as the screen. However, a previous blurring method on screen space has a drawback: the generated shadow is not correct when a view direction has a large angle to the normal of the shadowed plane. In this paper, we introduce a new screen space based method for soft shadowing that is fast and generates soft shadows more accurately than the previous screen space soft shadow mapping method. The resultant images show shadows produced by our method just stand in the same place, while shadows by the previous method change in terms of penumbra while the view moves. Surprisingly, although our method is more complex than the previous method, the measurement results of the calculation time show our method is almost the same performance. This is because it controls the blurring area more accurately and thus successfully reduces multiplications for blurring.

A new stock index trend analysis approach is proposed in this paper, which is based on a newly developed signal decomposition approach - adaptive Fourier decomposition (AFD). AFD can effectively extract the signal's primary trend, which specifically suits the Dow Theory based technique analysis. The proposed approach integrates two different kinds of forecasting approaches, including the Dow theory the RBF neural network. Effectiveness of the proposed approach is assessed through comparison with the direct RBF neural network approach. The result is proved to be promising.