In this paper, we report the design of an organic thin-film transistor (OTFT) driver circuit for the actuator of an organic fluid pump, which can be integrated in a portable-size fully-organic artificial lung. Compared to traditional pump designs, lightness, compactness and scalability are achieved by adopting a creative pumping mechanism with a completely organic-material-based system concept. The transportable fluid volume is verified to be flexibly adjustable, enabling on-demand controllability and scalability of the pump's fluid-flow rate. The simulations, based on an accurate surface-potential OTFT compact model, demonstrate that the necessary driving waveforms can be efficiently generated and adjusted to the actuator requirements. At the actuator-driving-circuit frequency of 0.98Hz, an all-organic fluid pump with 40cm length and 0.2cm height is able to achieve a flow rate of 0.847L/min, which satisfies the requirements for artificial-lung assist systems to a weakened normal lung.

This paper presents efficient and easily implementable methods for the characteristic analysis and tolerance analysis of nonlinear resistive circuits using integer programming. In these methods, the problem of finding all characteristic curves or all solution sets (regions of possible operating points) is formulated as a mixed integer programming problem, and it is solved by a high-performance integer programming solver such as CPLEX. It is shown that the proposed methods can easily be implemented without making complicated programs, and that all characteristic curves or all solution sets are obtained by solving mixed integer programming problems several times. Numerical examples are given to confirm the effectiveness of the proposed methods.

In this paper, a novel approach of a human motion classification system in wireless body area network (WBAN) using received radio signal strength was developed. This method enables us to classify human motions in WBAN using only the radio signal strength during communication without additional tools such as an accelerometer. The proposed human motion classification system has a potential to be used for improving communication quality in WBAN as well as recording daily-life activities for self-awareness tool. To construct the classification system, a numerical simulation was used to generate WBAN propagation channel in various motions at frequency band of 403.5MHz and 2.45GHz. In the classification system, a feature vector representing a characteristic of human motions was computed from time-series received signal levels. The proposed human motion classification using the radio signal strength based on WBAN simulation can classify 3-5 human motions with the accuracy rate of 63.8-95.7 percent, and it can classify the human motions regardless of frequency band. In order to confirm that the human motion classification using radio signal strength can be used in practice, the applicability of the classification system was evaluated by WBAN measurement data.

Traffic is a key aspect of everyday life. Its study, as it happens with other complex phenomena, has found in simulation a basic tool. However, the use of simulations faces important limitations. Building them requires considering different aspects of traffic (e.g. urbanism, car features, and individual drivers) with their specific theories, that must be integrated to provide a coherent model. There is also a variety of simulation platforms with different requirements. Many of these problems demand multi-disciplinary teams, where the different backgrounds can hinder the communication and validation of simulations. The Model-Driven Engineering (MDE) of simulations has been proposed in other fields to address these issues. Such approaches develop graphical Modelling Languages (MLs) that researchers use to model their problems, and then semi-automatically generate simulations from those models. Working in this way promotes communication, platform independence, incremental development, and reutilisation. This paper presents the first steps for a MDE framework for traffic simulations. It introduces a tailored extensible ML for domain experts. The ML is focused on human actions, so it adopts an Agent-Based Modelling perspective. Regarding traffic aspects, it includes concepts commonly found in related literature following the Driver-Vehicle-Environment model. The language is also suitable to accommodate additional theories using its extension mechanisms. The approach is supported by an infrastructure developed using Eclipse MDE projects: the ML is specified with Ecore, and a model editor and a code generator tools are provided. A case study illustrates how to develop a simulation based on a driver's behaviour theory for a specific target platform using these elements.

A simplified circuit has been utilized for fast computation of the current flowing in the cross-point memory array. However, the circuit has a constraint in that the selected cell is located farthest from current drivers so as to estimate the current degraded by metal wire resistance. This is because the length of the current path along the metal wire varies with the selected address in the cross-point memory array. In this paper, a new simplified circuit is proposed for calculating the current at every address in order to take account of the metal wire resistance. By employing the Monte Carlo simulation to solve the proposed simplified circuit, the current distribution across the array is obtained, so that failure rates of read disturbance and write error are estimated precisely. By comparing the conventional and the proposed simplified circuits, it was found that the conventional simplified circuit estimated optimistic failure rates for read disturbance and for write error when the wire resistance was prominent enough as a parasitic resistance.

This paper describes a hierarchical and cooperative transport system with demand responsive buses to improve service quality of public transport system in city area and its suburbs. To provide the demand responsive buses generally requires planning route and schedule called dial-a-ride problem. However, the problem complexity increases with the increasing of the number of requests. Therefore, we propose the hierarchical and cooperative transport system. Framework of the system can reduce scale of the problem by grouping customers. We have evaluated the proposed system on a static simulation and a dynamic microscopic simulation. The simulation result has shown the system could improve service quality by reducing customer's load. Moreover, the result of the dynamic simulation have provided the detailed features of the system.

In this paper, the repeatable hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. The authors' had previously proposed a hybrid parallel algorithm for inverse matrix computation. It is reasonably fast for a one time computation of an inverse matrix, but it is hard to apply this algorithm repeatedly for consecutive computations since the relocation of the large matrix is required at the beginning of each iterations. In order to eliminate the relocation of the large input matrix which is the output of the inverse matrix computation from the previous time step, the computation algorithm has been redesigned so that the required portion of the input matrix becomes the same as the output portion of the previously computed matrix in each node. This makes it possible to repeatedly and efficiently apply the SMW formula to compute inverse matrix in a time-series simulation.

An earthquake is a destructive natural disaster, which cannot be predicted accurately and causes devastating damage and losses. In fact, many of the damages can be prevented if people know what to do during and after earthquakes. Earthquake education is the most important method to raise public awareness and mitigate the damage caused by earthquakes. Generally, earthquake education consists of conducting traditional earthquake drills in schools or communities and experiencing an earthquake through the use of an earthquake simulator. However, these approaches are unrealistic or expensive to apply, especially in underdeveloped areas where earthquakes occur frequently. In this paper, an earthquake drill simulation system based on virtual reality (VR) technology is proposed. A User is immersed in a 3D virtual earthquake environment through a head mounted display and is able to control the avatar in a virtual scene via Kinect to respond to the simulated earthquake environment generated by SIGVerse, a simulation platform. It is a cost effective solution and is easy to deploy. The design and implementation of this VR system is proposed and a dormitory earthquake simulation is conducted. Results show that powerful earthquakes can be simulated successfully and the VR technology can be applied in the earthquake drills.

Controlling fluid simulation is one of the important research topics in computer graphics. In this paper, we focus on controlling the simulation of cumuliform cloud formation. Using a previously proposed method for controlling cloud simulation the convergence speed is very slow; therefore, it takes a long time before the clouds form the desired shapes. We improved the method and accelerated the convergence by introducing a new mechanism for controlling the amount of water vapor added. We demonstrate the effectiveness of the proposed method by several examples.

In this paper, we study on an availability analysis for a multibase system with lateral resupply of spare items between bases. We construct a basic model that a spare item of a base is transported for operation to another base without spare upon occurrence of failure, and simultaneously, the base that supplies the spare item receives the failed item of the other base for repair. We propose an approximation method to obtain the availability of the system and show the accuracy of the solution through numerical experiments. Also, two modified models are constructed to show the efficiency of the basic model. The two models modify the assumption on the lateral resupply of spare items between bases in the basic model. We numerically illustrate that the basic model can increase the availability of the system compared with the two modified models through Monte Carlo simulation.

Multi-agent based simulation has been widely used in behavior finance, and several single-processed simulation platforms with Agent-Based Modeling (ABM) have been proposed. However, traditional simulations of stock markets on single processed computers are limited by the computing capability since financial researchers need larger and larger number of agents and more and more rounds to evolve agents' intelligence and get more efficient data. This paper introduces a distributed multi-agent simulation platform, named PSSPAM, for stock market simulation focusing on large scale of parallel agents, communication system and simulation scheduling. A logical architecture for distributed artificial stock market simulation is proposed, containing four loosely coupled modules: agent module, market module, communication system and user interface. With the customizable trading strategies inside, agents are deployed to multiple computing nodes. Agents exchange messages with each other and with the market based on a customizable network topology through a uniform communication system. With a large number of agent threads, the round scheduling strategy is used during the simulation, and a worker pool is applied in the market module. Financial researchers can design their own financial models and run the simulation through the user interface, without caring about the complexity of parallelization and related problems. Two groups of experiments are conducted, one with internal communication between agents and the other without communication between agents, to verify PSSPAM to be compatible with the data from Euronext-NYSE. And the platform shows fair scalability and performance under different parallelism configurations.

In this paper the amplitude probability distribution (APD) measurement method is applied to evaluate noise coupling to an antenna on an evaluation board that uses mixed RF and digital signals of an IC. We analytically investigate noise coupling path to the antenna where the correlation coefficient matches the APD curve of the evaluation board. Moreover, in order to verify the analysis results, the noise coupling path in the board is evaluated by measurements involving In-phase/Quadrature (I/Q) signals as well as electromagnetic simulations. As a result, we demonstrate that APD method is effective in evaluating a degree of noise coupling from an IC to multiple antennas on the board, and confirm that the intensity of noise coupling to each antenna is affected greatly by the board layout patterns.

Verification of a design with respect to its requirement specification is important to prevent errors before constructing an actual implementation. The existing works focus on verifications where the specifications are described using temporal logics or using the same languages as that used to describe the designs. Our work considers cases where the specifications and the designs are described using different languages. To verify such cases, we propose a framework to check if a design conforms to its specification based on their simulation relation. Specifically, we define the semantics of the specifications and the designs commonly as labelled transition systems (LTSs). We appreciate LTSs since they could interpret information about the system and actions that the system may perform as well as the effect of these actions. Then, we check whether a design conforms to its specification based on the simulation relation of their LTS. In this paper, we present our framework for the verification of reactive systems, and we present the case where the specifications and the designs are described in Event-B and Promela/Spin, respectively. We also present two case studies with the results of several experiments to illustrate the applicability of our framework on practical systems.

This paper focuses on system level simulation of heterogeneous networks (HetNet). Aiming at the imbalance offloading of macro cell and pico cell under the macro-pico coexistence case, we propose an adaptive cell-specific association strategy for HetNet to ensure that users can be served equitably by both macro cell and pico cell. The traditional cell range expansion (CRE) scheme with bias-based cell association has fixed bias values for all pico cells. Our proposal, on the other hand, sets different thresholds of attached users for all MeNB (macro enhanced node B) and PeNBs (pico enhanced node B), and all cell-specific biases are obtained by the proposed adaptive association strategy according to different cell-specific predefined thresholds. With this strategy, the load imbalance between MeNB and different PeNBs is well alleviated, and hence the entire network performance is elevated. Moreover, due to the newly deployed low-power nodes in HetNets, the achieved spectral efficiency of users, especially for cell edge users, is also affected by the downlink inter-cell interference. The idea we put forward is to combine the frequency and power coordination, and so suppress the inter-cell interference. Finally in this paper, we present some numerical results to verify the effectiveness of our proposed approach.

The short-channel effect (SCE) in a MOSFET with an atomically thin MoS$_{2}$ channel was studied using a TCAD simulator. We derived the surface potential roll-up, drain-induced barrier lowering (DIBL), threshold voltage, and subthreshold swing (SS) as indexes of the SCE and analyzed their dependency on the channel thickness (number of atomic layers) and channel length. The minimum scalable channel length for a one-atomic-layer-thick MoS$_{2}$ MOSFET was determined from the threshold voltage roll-off to be 7.6,nm. The one-layer-thick device showed a small DIBL of 87,mV/V at a 20 nm gate length. By using high-k gate insulator, an SS lower than 70,mV/dec is achievable in sub-10-nm-scale devices.

The fast multipole method (FMM) for N-body simulations is attracting much attention since it requires minimal communication between computing nodes. We implemented hardware pipelines specialized for the FMM on an FPGA device, the GRAPE-9. An N-body simulation with 1.6×107 particles ran 16 times faster than that on a CPU. Moreover the particle-to-particle stage of the FMM on the GRAPE-9 executed 2.5 times faster than on a GPU in a limited case.

In this paper, we discuss performance modeling of 3-D stencil computing on an FPGA accelerator with a high-level synthesis environment, aiming for efficient exploration of user-space design parameters. First, we analyze resource utilization and performance to formulate these relationships as mathematical models. Then, in order to evaluate our proposed models, we implement heat conduction simulations as a benchmark application, by using MaxCompiler, which is a high-level synthesis tool for FPGAs, and MaxGenFD, which is a domain specific framework of the MaxCompiler for finite-difference equation solvers. The experimental results with various settings of architectural design parameters show the best combination of design parameters for pipeline structure can be systematically found by using our models. The effects of changing arithmetic accuracy and using data stream compression are also discussed.

Password-protected secret sharing (PPSS, for short) schemes were proposed by Bagherzandi, Jarecki, Saxena and Lu. In this paper, we consider another attack for PPSS schemes which is based on public parameters and documents. We show that the protocol proposed by Bagherzandi et al. is broken with the attack. We then propose an enhanced protocol which is secure against the attack.

The excessively high temperature in a chip may cause circuit malfunction and performance degradation, and thus should be avoided to improve system reliability. In this paper, a novel oscillation-based on-chip thermal sensing architecture for dynamically adjusting supply voltage and clock frequency in System-on-a-Chip (SoC) is proposed. It is shown that the oscillation frequency of a ring oscillator reduces linearly as the temperature rises, and thus provides a good on-chip temperature sensing mechanism. An efficient Dynamic Voltage-to-Frequency Scaling (DF2VS) algorithm is proposed to dynamically adjust supply voltage according to the oscillation frequencies of the ring oscillators distributed in SoC so that thermal sensing can be carried at all potential hot spots. An on-chip Dynamic Voltage Scaling or Dynamic Voltage and Frequency Scaling (DVS or DVFS) monitor selects the supply voltage level and clock frequency according to the outputs of all thermal sensors. Experimental results on SoC benchmark circuits show the effectiveness of the algorithm that a 10% reduction in supply voltage alone can achieve about 20% power reduction (DVS scheme), and nearly 50% reduction in power is achievable if the clock frequency is also scaled down (DVFS scheme). The chip temperature will be significant lower due to the reduced power consumption.

Positive real approximation of sampled frequency data obtained from electromagnetic analysis or measurement is presented. The proposed two methods are based on the Fourier expansion method. The frequency data are approximated by the Laguerre series that becomes the Fourier series with an infinite interval at an imaginary axis of complex plane. The proposed methods do not require any passivity check algorithm. The first method approximates the real parts of sampled data by the piecewise linear matrix function. The second method uses discrete Fourier transform. It is here proven that the approximated matrix function is an interpolative function for the real parts of sampled data. The proposed methods are applied to the approximation of per unit length parameters of multi-conductor system. The capability of the proposed methods is demonstrated.