On-line object tracking (OLOT) has been a core technology in computer vision, and its importance has been increasing rapidly. Because this technology is utilized for battery-operated products, energy consumption must be minimized. This paper describes a method of adaptive frame-rate optimization to satisfy that requirement. An energy trade-off occurs between image capturing and object tracking. Therefore, the method optimizes the frame-rate based on always changed object speed for minimizing the total energy while taking into account the trade-off. Simulation results show a maximum energy reduction of 50.0%, and an average reduction of 35.9% without serious tracking accuracy degradation.

In this study, spatially coupled low-density parity-check (SC-LDPC) codes on the two-dimensional array erasure (2DAE) channel are devised, including a method for generating new SC-LDPC codes with a restriction on the check node constraint. A density evolution analysis confirms the improvement in the threshold of the proposed two-dimensional SC-LDPC code ensembles over the one-dimensional SC-LDPC code ensembles. We show that the BP threshold of the proposed codes can approach the corresponding maximum a posteriori (MAP) threshold of the original residual graph on the 2DAE channel. Moreover, we show that the rates of the residual graph of the two-dimensional LDPC block code ensemble are smaller than those of the one-dimensional LDPC block code ensemble. In other words, a high performance can be obtained by choosing the two-dimensional SC-LDPC codes.

Racetrack memory (RM) has attracted much attention. In RM, insertion and deletion (ID) errors occur as a result of an unstable reading process and are called position errors. In this paper, we first define a probabilistic channel model of ID errors in RM with multiple read-heads (RHs). Then, we propose a joint iterative decoding algorithm for spatially coupled low-density parity-check (SC-LDPC) codes over such a channel. We investigate the asymptotic behaviors of SC-LDPC codes under the proposed decoding algorithm using density evolution (DE). With DE, we reveal the relationship between the number of RHs and achievable information rates, along with the iterative decoding thresholds. The results show that increasing the number of RHs provides higher decoding performances, although the proposed decoding algorithm requires each codeword bit to be read only once regardless of the number of RHs. Moreover, we show the performance improvement produced by adjusting the order of the SC-LDPC codeword bits in RM.

The construction of frequency hopping sequences with good Hamming correlation is the foundation of research in frequency hopping communication. In this letter, classes of optimal low hit zone frequency hopping sequence set are constructed based on the interleaving technology. The results of the study show that the sequence set with large family size is optimal for the Peng-Fan-Lee bound. And all the sequences in the set are inequivalent.

This study proposes a multiple-output differential-input operational transconductance amplifier-C (MODI OTA-C) filter with an impedance scaler to detect cardiac activity. A ladder-type fifth-orderButterworth low-pass filter with a large time constant and low noise is implemented to reduce coefficient sensitivity and address signal distortion. Moreover, linearized MODI OTA structures with reduced transconductance and impedance scaler circuits for noise reduction are used to achieve a wide dynamic range (DR). The OTA-based circuit is operated in the subthreshold region at a supply voltage of 1 V to reduce the power consumption of the wearable device in long-term use. Experimental results of the filter with a bandwidth of 250 Hz reveal that DR is 57.6 dB, and the harmonic distortion components are below -59 dB. The power consumption of the filter, which is fabricated through a TSMC 0.18 µm CMOS process, is lower than 390 nW, and the active area is 0.135 mm2.

This paper describes a broadband low phase noise VCO implemented in 0.13 µm CMOS process. A 1-bit switched varactor and a 4-bit capacitor array are adopted in cooperation with the automatic frequency calibration (AFC) circuit to lower the VCO tuning gain (KVCO), with a measured AFC time of 6 µs. Several noise reduction techniques are exploited to minimize the phase noise of the VCO. Measurement results show the VCO generates a high frequency range from 11.37 GHz to 14.8 GHz with a KVCO of less than 270 MHz/V. The prototype exhibits a phase noise of -114.6 dBc/Hz @ 1 MHz at 14.67 GHz carrier frequency and draws 10.5 mA current from a 1.2 V supply. The achieved figure-of-merits (FoM=-186.9dBc/Hz, FoMT=-195.3dBc/Hz) favorably compares with the state-of-the-art.

By exploiting the inherent sparsity of wireless channels, the channel estimation in an orthogonal frequency division multiplexing (OFDM) system can be cast as a compressed sensing (CS) problem to estimate the channel more accurately. Practically, matching pursuit algorithms such as orthogonal matching pursuit (OMP) are used, where path delays of the channel is guessed based on correlation values for every quantized delay with residual. This full search approach requires a predefined grid of delays with high resolution, which induces the high computational complexity because correlation values with residual at a huge number of grid points should be calculated. Meanwhile, the correlation values with high resolution can be obtained by interpolation between the correlation values at a low resolution grid. Also, the interpolation can be implemented with a low pass filter (LPF). By using this fact, in this paper we substantially reduce the computational complexity to calculate the correlation values in channel estimation using CS.

Security facilities such as firewall system and IDS/IPS (Intrusion Detection System/Intrusion Prevention System) have become fundamental solutions against cyber threats. With the rapid change of cyber attack tactics, detail investigations like DPI (Deep Packet Inspection) and SPI (Stateful Packet Inspection) for incoming traffic become necessary while they also cause the decrease of network throughput. In this paper, we propose an SDN (Software Defined Network) - based proactive firewall system in collaboration with domain name resolution to solve the problem. The system consists of two firewall units (lightweight and normal) and a proper one will be assigned for checking the client of incoming traffic by the collaboration of SDN controller and internal authoritative DNS server. The internal authoritative DNS server obtains the client IP address using EDNS (Extension Mechanisms for DNS) Client Subnet Option from the external DNS full resolver during the name resolution stage and notifies the client IP address to the SDN controller. By checking the client IP address on the whitelist and blacklist, the SDN controller assigns a proper firewall unit for investigating the incoming traffic from the client. Consequently, the incoming traffic from a trusted client will be directed to the lightweight firewall unit while from others to the normal firewall unit. As a result, the incoming traffic can be distributed properly to the firewall units and the congestion can be mitigated. We implemented a prototype system and evaluated its performance in a local experimental network. Based on the results, we confirmed that the prototype system presented expected features and acceptable performance when there was no flooding attack. We also confirmed that the prototype system showed better performance than conventional firewall system under ICMP flooding attack.

In this paper, we devise low-complexity uplink detection algorithms for Massive MIMO systems. We treat the uplink detection as an ill-posed problem and adopt the Landweber Method to solve it. In order to reduce the computational complexity and increase the convergence rate, we propose improved Landweber Method with optimal relax factor (ILM-O) algorithm. In addition, to reduce the order of Landweber Method by introducing a set of coefficients, we propose reduced order Landweber Method (ROLM) algorithm. An analysis on the convergence and the complexity is provided. Numerical results demonstrate that the proposed algorithms outperform the existing algorithm.

This paper presents an efficient acceleration algorithm for Lloyd-type k-means clustering, which is suitable to a large-scale and high-dimensional data set with potentially numerous classes. The algorithm employs a novel projection-based filter (PRJ) to avoid unnecessary distance calculations, resulting in high-speed performance keeping the same results as a standard Lloyd's algorithm. The PRJ exploits a summable lower bound on a squared distance defined in a lower-dimensional space to which data points are projected. The summable lower bound can make the bound tighter dynamically by incremental addition of components in the lower-dimensional space within each iteration although the existing lower bounds used in other acceleration algorithms work only once as a fixed filter. Experimental results on large-scale and high-dimensional real image data sets demonstrate that the proposed algorithm works at high speed and with low memory consumption when large k values are given, compared with the state-of-the-art algorithms.

In this paper, we review a super-steep subthreshold slope (SS) (<1 mV/dec) body-tied (BT) silicon on insulator (SOI) metal oxide semiconductor field effect transistor (MOSFET) fabricated with 0.15 µm SOI technology and discuss the possibility of its use in ultralow voltage applications. The mechanism of the super-steep SS in the BT SOI MOSFET was investigated with technology computer-aided design simulation. The gate length/width and Si thickness optimizations promise further reductions in operation voltage, as well as improvement of the ION/IOFF ratio. In addition, we demonstrated control of the threshold voltage and hysteresis characteristics using the substrate and body bias in the BT SOI MOSFET.

In this paper, we propose an IEEE 802.15.10-based layer 2 routing (L2R) method with a load balancing algorithm; the proposal considers fairness in terms of the cumulative number of sending packets at each terminal to resolve the packet concentration problem for the IEEE 802.15.4-based low-power consumption wireless smart utility network (Wi-SUN) systems. The proposal uses the accumulated sending times of each terminal as a weight in calculating each path quality metric (PQM) to decide multi-hopping routes with load balancing in the network. Computer simulation of the mesh network with 256 terminals shows that the proposed routing method can improve the maximum sending ratio (MSR), defined as the ratio of the maximum sending times to the average number of sending times in the network, by 56% with no degradation of the end-to-end communication success ratio (E2E-SR). The proposed algorithm is also experimentally evaluated by using actual Wi-SUN modules. The proposed routing method also improves the MSR by 84% with 70 terminals. Computer simulations and experiments prove the effectiveness of the proposed method in terms of load balancing.

This paper describes a novel composite right-/left-handed (CRLH) transmission line (TL) stub resonator for X-band low phase-noise oscillator application. The bandpass filter type resonator composed only of microstrip components exhibits unloaded-Q exceeding that of microstrip-line resonators by engineering the dispersion relation for the CRLH TL. Two different types of stub resonator using identical and non-identical unit-cells are compared. Although the latter type was found to be superior to the former in terms of spurious frequency responses and the circuit size, care was taken to prevent the parasitic inductances distributed in the interdigital capacitors from impeding the Q-factor control capability of the resonator. The stub resonator thus optimized was applied to an 8.8-GHz SiGe HBT oscillator, which achieved a phase-noise of -134dBc/Hz at 1-MHz offset despite the modest dielectric loss tangent of the PCB laminate used as the substrate of the circuit.

In many communications applications, maximum-likelihood decoding reduces to solving an integer least-squares problem, which is NP-hard in the worst case. It has recently been shown that over a wide range of dimensions and SNRs, the branch and bound (BB) algorithm can be used to find the exact solution with an expected complexity that is roughly cubic in the dimension of the problem. However, the computational complexity becomes prohibitive if the SNR is too low and/or the dimension of the problem is too large. The dichotomous coordinate descent (DCD) algorithm provides low complexity, but its detection performance is not as good as that of the BB detector. Two methods are developed to bound the optimal detector cost to reduce the complexity of BB in this paper. These methods are DCD-based detectors for MIMO and multiuser detection in the scenario of a large number of transmitting antennas/users. First, a combined detection technique based on the BB and DCD algorithms is proposed. The technique maintains the advantages of both algorithms and achieves a good trade-off between performance and complexity compared to using only the BB or DCD algorithm. Second, since the first feasible solution obtained from the BB search is the solution of the decorrelating decision feedback (DF) method and because DCD results in better accuracy than the decorrelating DF solution, we propose that the first feasible solution of the BB algorithm be obtained by the box-constrained DCD algorithm rather than the decorrelating DF detector. This method improves the precision of the initial solution and identifies more branches that can be eliminated from the search tree. The results show that the DCD-based BB detector provides optimal detection with reduced worst-case complexity compared to that of the decorrelating DF-based BB detector.

To completely utilize the advantages of dynamic voltage and frequency scaling (DVFS) techniques, a quantized decoder (QNT-D) was developed. The QNT-D generates a quantized signal processing quantity (Q) using a predicted signal processing quantity (M). Q is used to produce the optimum frequency (opt.fc) and the optimum supply voltage (opt.VD) that are proportional to Q. To develop a DVFS controlled motion estimation (ME) processor, we used both the QNT-D and a fast ME algorithm called A2BC (Adaptively Assigned Breaking-off Condition) to predict M for each macro-block (MB). A DVFS controlled ME processor was fabricated using 90-nm CMOS technology. The total power dissipation (PT) of the processor was significantly reduced and varied from 38.65 to 99.5 µW, only 3.27 to 8.41 % of PT of a conventional ME processor, depending on the test video picture.

We are developing an Ultra-Low Field (ULF) Magnetic Resonance Imaging (MRI) system with a tuned high-Tc (HTS)-rf-SQUID for food inspection. We previously reported that a small hole in a piece of cucumber can be detected. The acquired image was based on filtered back-projection reconstruction using a polarizing permanent magnet. However the resolution of the image was insufficient for food inspection and took a long time to process. The purpose of this study is to improve image quality and shorten processing time. We constructed a specially designed cryostat, which consists of a liquid nitrogen tank for cooling an electromagnetic polarizing coil (135mT) at 77K and a room temperature bore. A Cu pickup coil was installed at the room temperature bore and detected an NMR signal from a sample. The signal was then transferred to an HTS SQUID via an input coil. Following a proper MRI sequence, spatial frequency data at 64×32 points in k-space were obtained. Then, a 2D-FFT (Fast Fourier Transformation) method was applied to reconstruct the 2D-MR images. As a result, we successfully obtained a clear water image of the characters “TUT”, which contains a narrowest width of 0.5mm. The imaging time was also shortened by a factor of 10 when compared to the previous system.

This letter describes a method that characterizes and improves the performance of a time-interleaved (TI) digital-to-analog converter (DAC) system by using multiport signal-flow graphs at microwave frequencies. A commercial signal generator with two TI DACs was characterized through s-parameter measurements and was compared to the conventional method. Moreover, prefilters were applied to correct the response, resulting in an error-vector magnitude improvement of greater than 8 dB for a 64-quadrature-amplitude-modulated signal of 4.8 Gbps. As a result, the bandwidth limitation and the complex post processing of the conventional method could be minimized.

In X-ray computed tomography, scattered X-rays are generally removed by using a post-patient collimator located in front of the detector. In this paper, we show that the scattered X-rays have the potential to improve the estimation accuracy of the attenuation coefficient in computed tomography. In order to clarify the problem, we simplified the geometry of the computed tomography into a thin cylinder composed of a homogeneous material so that only one attenuation coefficient needs to be estimated. We then conducted a Monte Carlo numerical experiment on improving the estimation accuracy of attenuation coefficient by measuring the scattered X-rays with several dedicated toroidal detectors around the cylinder in addition to the primary X-rays. We further present a theoretical analysis to explain the experimental results. We employed a model that uses a T-junction (i.e., T-junction model) to divide the photon transport into primary and scattered components. This division is processed with respect to the attenuation coefficient. Using several T-junction models connected in series, we modeled the case of several scatter detectors. The estimation accuracy was evaluated according to the variance of the efficient estimator, i.e., the Cramer-Rao lower bound. We confirmed that the variance decreases as the number of scatter detectors increases, which implies that using scattered X-rays can reduce the irradiation dose for patients.

To deal with the reliability issue caused by soft errors, this paper proposed a low power soft error hardened latch (SHC) design using a novel Schmitt-Trigger-based C-element for reliable low power applications. Unlike state-of-the-art soft error tolerant latches that are usually based on hardware redundancy with large area overhead and high power consumption, the proposed SHC latch is implemented through double-sampling and node-checking using a novel Schmitt-Trigger-based C-element, which can help to reduce the area overhead and the corresponding power consumption as well. The evaluation results show that the total number of transistors of the proposed SHC latch is only increased by 2 when compared to the conventional unhardened C2MOS latch, while up to 20.35% and 82.96% power reduction can be achieved when compared to the conventional unhardened C2MOS latch and the existing soft error tolerant HiPeR design, respectively.

With the rapid increase in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying wireless local area network (LAN) hotspots on to which they can offload their mobile traffic. However, these network-centric methods usually do not fulfill the interests of mobile users (MUs). Taking into consideration many issues such as different applications' deadlines, monetary cost and energy consumption, how the MU decides whether to offload their traffic to a complementary wireless LAN is an important issue. Previous studies assume the MU's mobility pattern is known in advance, which is not always true. In this paper, we study the MU's policy to minimize his monetary cost and energy consumption without known MU mobility pattern. We propose to use a kind of reinforcement learning technique called deep Q-network (DQN) for MU to learn the optimal offloading policy from past experiences. In the proposed DQN based offloading algorithm, MU's mobility pattern is no longer needed. Furthermore, MU's state of remaining data is directly fed into the convolution neural network in DQN without discretization. Therefore, not only does the discretization error present in previous work disappear, but also it makes the proposed algorithm has the ability to generalize the past experiences, which is especially effective when the number of states is large. Extensive simulations are conducted to validate our proposed offloading algorithms.