To improve the outage performance of a wireless body area network (BAN), exploitation of the diversity in the channel obtained by letting different nodes cooperate and relay signals for each other is an attractive solution. We carry out multi-link channel measurements and modeling for all realistic locations of the on-body sensor nodes and for three different motion scenarios in a typical office environment to develop equivalent channel model for simple and practical cooperative transmission schemes. Using the developed model the performance of the transmission schemes are evaluated and compared. Incremental decode and forward relaying is found to be consistently better than the other schemes with gains of up to 16dB at 10% outage probability, and an average gain of more than 5.9dB for any location of the coordinator node. The best location of the coordinator node based on the performance is also determined. Such insights will be very useful in designing BANs.

The ultimate purpose of a business process is to promote business values. Thus, any process that fails to enhance or promote business values should be improved or adjusted so that business values can be achieved. Therefore an organization should have the capability of confirming whether a business value is achieved; furthermore, in order to cope with the changes of business environment, it should be able to define the necessary measures on the basis of business values. This paper proposes techniques for measuring a business process based on business values, which can be used to monitor and control business activities focusing on the attainment of business values. To show the feasibility of the techniques, we compare their monitoring and controlling capabilities with those of the current fulfillment process of a company. The results show that the proposed techniques are effective in linking business values to relevant processes and integrating each measurement result in accordance with the management level.

Electrostatic discharge (ESD) generators cause electromagnetic (EM) noises not only at ESD tests but also even before and after the tests. This may provide inconsistent test results, but the mechanism has not been well examined. To explain the mechanism qualitatively, we investigated a generation source model of EM noises from an ESD generator in conjunction with the functional control sequences of built-in relay switches and the DC high voltage power supply. To validate this model, we used a magnetic field probe to measure the induced EM noises before, during, and after contact and air discharges in accordance with the corresponding timing of the functional control sequences. As a result, we confirmed that the EM noises are induced when the relay switches operate before and at ESD testing and after ESD tests for both contact and air discharges. In addition, we found that the noise peaks due to contact discharges increase with charge voltages, and the peaks just before and at the testing are relatively larger than the ones after the tests, while the peaks of the induced noises at the air discharge testing do not always increase with charge voltages, but reach a maximum at 3kV. In addition, the peaks of the induced noises at the air discharge testing become smaller than either the peaks just before the testing and those after the tests at charge voltages above 6kV. This suggests that the EM noises just before ESD testing and after the test may cause the EUT to malfunction when air discharge tests with charge voltages over 6kV are conducted. A new control sequence of the built-in relay switch was also proposed for reducing the EM noises after ESD tests, which was validated through noise measurements.

For compressed sensing, to address problems which do not involve reconstruction, a correlation analysis between measurements and the transform coefficients is proposed. It is shown that there is a linear relationship between them, which indicates that we can abstract the inner property of images directly in the measurement domain.

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.

We propose a method to extract scene situation by orientation sensors of multiple mobile phones' environment. By using orientations recorded with videos, we analyzed their view concentrations as a remarkable position of the scene for each frame of videos. In an experiment for a soccer scene, the extracted points can be related to a trajectory of a soccer ball.

A simple, low reflection, and highly-efficient pilot-plant scale microwave irradiation reactor for woody biomass pretreatment was fabricated. Pretreatment is an essential process for effective bioethanol production. The fabricated reactor consists of 8 microwave irradiators which are attached to a metal pipe. The woody biomass mixture which contains water and organic acid flows through the metal pipe and is heated by microwaves at a total power of 12,kW. To design the microwave irradiators, we used a 3D Finite Element Method (FEM) simulator, which was based on the measured complex permittivity data of the woody biomass mixture. The simulation results showed that the reflection coefficient $|S_{11}|$ from the reactor was less than -30,dB when the woody biomass mixture temperature was between 30$^{circ}$C and 90$^{circ}$C. Finally, we experimentally confirmed that the fabricated irradiation reactor yielded a microwave absorption efficiency of 79%.

More recently, there has been a growing interest in the study of wireless sensor network (WSN) technologies for Interest of Things (IoT). To improve the positioning accuracy of mobile station under the non-line-of-sight (NLOS) environment, a localization algorithm based on the single-hidden layer feedforward network (SLFN) using extreme learning machine (ELM) for WSN is proposed in this paper. Optimal reduction in the time difference of arrival (TDOA) measurement error is achieved using SLFN optimized by ELM. Compared with those traditional learning algorithms, ELM has its unique feature of a higher generalization capability at a much faster learning speed. After utilizing the ELM by randomly assigning the parameters of hidden nodes in the SLFN, the competitive performance can be obtained on the optimization task for TDOA measurement error. Then, based on that result, Taylor algorithm is implemented to deal with the position problem of mobile station. Experimental results show that the effect of NLOS propagation is reduced based on our proposed algorithm by introducing the ELM into Taylor algorithm. Moreover, in the simulation, the proposed approach, called Taylor-ELM, provides better performance compared with some traditional algorithms, such as least squares, Taylor, backpropagation neural network based Taylor, and Chan positioning methods.

This paper describes numerical analyses of the distance-dependent gain variation that exists in gain measurements based on the Friis transmission formula for typical broadband antennas, including double-ridged guide horn and log-periodic dipole array antennas. The analyses are performed by simulating gain measurements using the method of moments with higher-order basis functions and the finite integration method. In addition, we propose approximate techniques to determine the antenna phase center by exploiting the distance dependence of the gain. Simulation and experimental results show the effectiveness of using the location of the phase center to accurately determine the far-field gain at reduced antenna separation distances.

With the advent of high speed links, online flow measurement for, e.g., flow round trip time (RTT), has become difficult due to the enormous demands placed on computational resources. Most existing measurement methods are designed to count the numbers of flows or sizes of flows, but we address the flow RTT measurement, which is an important QoS metric for network management and cannot be measured with existing measurement methods. We first adapt a standard Bloom Filter (BF) for the flow RTT distribution estimation. However, due to the existence of multipath routing and Syn flooding attacks, the standard BF does not perform well. We further design the double-deletion bloom filter (DDBF) scheme, which alleviates potential hash collisions of the standard BF by explicitly deleting used records and implicitly deleting out-of-date records. Because of these double deletion operations, the DDBF accurately estimates the RTT distribution of TCP flows with limited memory space, even with the appearance of multipath routing and Syn flooding attacks. Theoretical analysis indicates that the DDBF scheme achieves a higher accuracy with a constant and smaller amount of memory compared with the standard BF. In addition, we validate our scheme using real traces and demonstrate significant memory-savings without degrading accuracy.

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.

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.

We propose a novel IDDQ outlier screening flow through a two-phase approach: a clustering-based filtering and an estimation-based current-threshold determination. In the proposed flow, a clustering technique first filters out chips that have high IDDQ current. Then, in the current-threshold determination phase, device-parameters of the unfiltered chips are estimated based on measured IDDQ currents through Bayesian inference. The estimated device-parameters will further be used to determine a statistical leakage current distribution for each test pattern and to calculate a and suitable current-threshold. Numerical experiments using a virtual wafer show that our proposed technique is 14 times more accurate than the neighbor nearest residual (NNR) method and can achieve 80% of the test escape in the case of small leakage faults whose ratios of leakage fault sizes to the nominal IDDQ current are above 40%.

Scheduling is a key problem in high level synthesis, as the scheduling results affect most of the important design metrics. In this paper, we propose a novel scheduling method to simultaneously optimize the leakage power of functional units with dual-Vth techniques and the number of registers under given timing and resource constraints. The mobility overlaps between operations are removed to eliminate data dependencies, and a simulated-annealing-based method is introduced to explore the mobility overlap removal solution space. Given the overlap-free mobilities, the resource usage and register usage in each control step can be accurately estimated. Meanwhile, operations are scheduled so as to optimize the leakage power of functional units with minimal number of registers. Then, a set of operations is iteratively selected, reassigned as low-Vth, and rescheduled until the resource constraints are all satisfied. Experimental results show the efficiency of the proposed algorithm.

A novel class of signal of perfect Gaussian integer sequence pairs are put forward in this paper. The constructions of obtaining perfect Gaussian integer sequence pairs of odd length by using Chinese remainder theorem as well as perfect Gaussian integer sequence pairs of even length by using complex transformation and interleaving techniques are presented. The constructed perfect Gaussian integer sequence pairs can not only expand the existence range of available perfect Gaussian integer sequences and perfect sequence pairs signals but also overcome the energy loss defects.

The relay channel is the common approach to cooperative communication. Quasi-cyclic low-density parity-check (QC-LDPC) code design for the relay channel is important to cooperative communication. This paper proposes a bilayer QC-LDPC code design scheme for the relay channel. Combined with the bilayer graphical code structure, an improved Chinese remainder theorem (CRT) method, the Biff-CRT method is presented. For the proposed method we introduce a finite field approach. The good performance of the finite field based QC-LDPC code can improve the performance of its corresponding objective QC-LDPC code in the proposed scheme. We construct the FF code and the FA code by the Biff-CRT method. The FF code and the FA code are both named as their two component codes. For the FF code, the two component code are both finite field based QC-LDPC codes. For the FA code, one of the component codes is the finite field based QC-LDPC code and the other is the array code. For the existing CRT method, the shortened array code and the array code are usually used as the component codes to construct the SA code. The exponent matrices of FF code, FA code and SA code are given both for the overall graph and the lower graph. Bit error rate (BER) simulation results indicate that the proposed FF code and FA code are superior to the SA code both at the relay node and the destination node. In addition, the theoretical limit and the BER of the bilayer irregular LDPC code are also given to compare with the BER of the proposed QC-LDPC codes. Moreover, the proposed Biff-CRT method is flexible, easy to implement and effective for constructing the QC-LDPC codes for the relay channel, and it is attractive for being used in the future cooperative communication systems.

This paper presents a measurement circuit structure for capturing SET pulse-width suppressing pulse-width modulation and within-die process variation effects. For mitigating pulse-width modulation while maintaining area efficiency, the proposed circuit uses massively parallelized short inverter chains as a target circuit. Moreover, for each inverter chain on each die, pulse-width calibration is performed. In measurements, narrow SET pulses ranging 5ps to 215ps were obtained. We confirm that an overestimation of pulse-width may happen when ignoring die-to-die and within-die variation of the measurement circuit. Our evaluation results thus point out that calibration for within-die variation in addition to die-to-die variation of the measurement circuit is indispensable.

In compressed sensing, the design of the measurement matrix is a key work. In order to achieve a more precise reconstruction result, the columns of the measurement matrix should have better orthogonality or linear incoherence. A random matrix, like a Gaussian random matrix (GRM), is commonly adopted as the measurement matrix currently. However, the columns of the random matrix are only statistically-orthogonal. By substituting an orthogonal basis into the random matrix to construct a semi-random measurement matrix and by optimizing the mutual coherence between dictionary columns to approach a theoretical lower bound, the linear incoherence of the measurement matrix can be greatly improved. With this optimization measurement matrix, the signal can be reconstructed from its measures more precisely.

The composite binary offset carrier (CBOC) modulated signal contains multi-peaks in its auto-correlation function, which brings ambiguity to the signal acquisition process of a GNSS receiver. Currently, most traditional ambiguity-removing schemes for CBOC signal acquisition approximate CBOC signal as a BOC signal, which may incur performance degradation. Based on Galileo E1 CBOC signal, this paper proposes a novel adaptive ambiguity-removing acquisition scheme which doesn't adopt the approximation used in traditional schemes. According to the energy ratio of each sub-code of CBOC signal, the proposed scheme can self-adjust its local reference code to achieve unambiguous and precise signal synchronization. Monte Carlo simulation is conducted in this paper to analyze the performance of the proposed scheme and three traditional schemes. Simulation results show that the proposed scheme has higher detection probability and less mean acquisition time than the other three schemes, which verify the superiority of the proposed scheme.