This paper proposes a mixed-grained reconfigurable architecture consisting of fine-grained and coarse-grained fabrics, each of which can be configured for different levels of reliability depending on the reliability requirement of target applications, e.g. mission-critical applications to consumer products. Thanks to the fine-grained fabrics, the architecture can accommodate a state machine, which is indispensable for exploiting C-based behavioral synthesis to trade latency with resource usage through multi-step processing using dynamic reconfiguration. In implementing the architecture, the strategy of dynamic reconfiguration, the assignment of configuration storage and the number of implementable states are key factors that determine the achievable trade-off between used silicon area and latency. We thus split the configuration bits into two classes; state-wise configuration bits and state-invariant configuration bits for minimizing area overhead of configuration bit storage. Through a case study, we experimentally explore the appropriate number of implementable states. A proof-of-concept VLSI chip was fabricated in 65nm process. Measurement results show that applications on the chip can be working in a harsh radiation environment. Irradiation tests also show the correlation between the number of sensitive bits and the mean time to failure. Furthermore, the temporal error rate of an example application due to soft errors in the datapath was measured and demonstrated for reliability-aware mapping.

With the shorter time-to-market and the rising cost in SoC development, the demand for post-silicon programmability has been increasing. Recently, programmable accelerators have attracted more attention as an enabling solution for post-silicon engineering change. However, programmable accelerators suffers from 5∼10X less energy efficiency than fixed-function accelerators mainly due to their extensive use of memories. This paper proposes a highly energy-efficient accelerator which enables post-silicon engineering change by a control patching mechanism. Then, we propose a patch compilation method from a given pair of an original design and a modified design. We also propose a design method to add redundant wires in advance to decrease the necessary amount of patch memory for post-silicon engineering change. Experimental results demonstrate that the proposed accelerators offer high energy efficiency competitive to fixed-function accelerators and can achieve about 5X higher efficiency than the existing programmable accelerators. We also show the trade-off between redundant wires and the necessary amount of patch memory.

DetF (Detect-and-Forward) is studied as a relay method in multi-hop networks. When an error detection scheme is introduced, DetF is likely to achieve an efficient transmission. In this study, AMI (Alternate Mark Inversion) code is focused on as an error detection scheme. Error detection performances of ternary PSK (Phase Shift Keying) using AMI code and binary PSK using parity check code are examined. It is shown that ternary PSK using AMI code has a good error detection performance.

Rate control that is required to regulate the bitrate of video coding is critical to time-sensitive video applications used over networks. However, the H.264/AVC standard does not respond to scene changes, and this causes the transmission quality to deteriorate as a scene change occurs. In this work, a scene change is detected by comparing the ratio of the sum of absolute difference (SAD) between two consecutive frames. As the scene change is detected, the proposed method, which is modified from the reference software of H.264/AVC, re-assigns a quantization parameter (QP) value to regulate the bitrate. Because the inter-prediction works poorly for the scene-changed frame, the proposed method estimates its frame complexity based on the content, and further creates another Q-R model to assign QP. The adaptive rate control mechanism presented in this study can quickly respond to the heavy bitrate increment caused by a change of scene. Simulation results show that the proposed method improves the average peak signal noise ratio (PSNR) to approximately 1.1dB, with a smaller buffer size compared with the performance of the reference software JM version 17.2.

Because of the popularity of rich content, such as video files, the amount of traffic on the Internet continues to grow every year. Not only is the overall traffic increasing, but also the temporal fluctuations in traffic are increasing, and differences in the amounts of traffic between peak and off-peak periods are becoming very large. Consequently, efficient use of link bandwidth is becoming more challenging. In this paper, we propose a new system for content distribution: storage aware routing (SAR). With SAR, routers having large storage capacities can exploit those links that are underutilized. Our performance evaluations show that SAR can smooth the fluctuations in link utilization.

This paper proposes to obtain high-level, domain-robust representations for cross-view face recognition. Specially, we introduce Convolutional Deep Belief Networks (CDBN) as the feature learning model, and an CDBN based interpolating path between the source and target views is built to model the correlation of cross-view data. The promising results outperform other state-of-the-art methods.

This paper proposes an ultra-low-voltage, wide signal swing, and clock-scalable differential dynamic amplifier using a common-mode voltage detection technique. The essential characteristics of an amplifier, such as gain, linearity, power consumption, noise, etc., are analyzed. In measurement, the proposed dynamic amplifier achieves a 13dB gain with less than 1dB drop over a differential output signal swing of 340mVpp with a supply voltage of 0.5V. The attained maximum operating frequency is 700MHz. With a 0.7V supply, the gain increases to 16dB with a signal swing of 700mVpp. The prototype amplifier is fabricated in 90nm CMOS technology with the low threshold voltage and the deep N-well options.

Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.

LED (Light Encryption Device) block cipher, one of lightweight block ciphers, is very compact in hardware. Its encryption process is composed of AES-like rounds. Recently, a scan-based side-channel attack is reported which retrieves the secret information inside the cryptosystem utilizing scan chains, one of design-for-test techniques. In this paper, a scan-based attack method on the LED block cipher using scan signatures is proposed. In our proposed method, we focus on a particular 16-bit position in scanned data obtained from an LED LSI chip and retrieve its secret key using scan signatures. Experimental results show that our proposed method successfully retrieves its 64-bit secret key using 36 plaintexts on average if the scan chain is only connected to the LED block cipher. These experimental results also show the key is successfully retrieved even if the scan chain includes additional 130,000 1-bit data.

An Invertible Bloom Lookup Tables (IBLT) is a data structure which supports insertion, deletion, retrieval and listing operations for the key-value pair. An IBLT can be used to realize efficient set reconciliation for database synchronization. The most notable feature of the IBLT is the complete listing operation of key-value pairs based on the algorithm similar to the peeling algorithm for low-density parity check (LDPC) codes. In this paper, we will present a stopping set (SS) analysis for the IBLT that reveals finite length behaviors of the listing failure probability. The key of the analysis is enumeration of the number of stopping matrices of given size. We derived a novel recursive formula useful for computationally efficient enumeration. An upper bound on the listing failure probability based on the union bound accurately captures the error floor behaviors.

A Balanced Neighborhood Classifier (BNEC) is proposed for class imbalanced data. This method is not only well positioned to capture the class distribution information, but also has the good merits of high-fitting-performance and simplicity. Experiments on both synthetic and real data sets show its effectiveness.

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.

This paper proposes a name-based routing mechanism called Routing Guidance Name (RGN) that offers new routing management functionalities within the basic characteristics of CCN. The proposed mechanism names each CCN router. Each router becomes a Data Provider for its name. When a CCN Interest specifies a router's name, it is forwarded to the target router according to the standard mechanism of CCN. Upon receiving an Interest, each router reacts to it according to RGN. This paper introduces a new type of node called a Scheduler which calculates the best routes based on link state information collected from routers. The scheduler performs its functions based on RGN. This paper discusses how the proposed system builds CCN FIB (Forwarding Information Base) in routers. The results of experiments reveal that RGN is more efficient than the standard CCN scheme. It is also shown that the proposal provides mobility support with short delay time. We explain a practical mobile scenario to illustrate the advantages of the proposal.

The development of high data rate wireless communications systems using Multiple Input — Multiple Output (MIMO) antenna techniques requires detectors with reduced complexity and good Bit Error Rate (BER) performance. In this paper, we present the Semi-fixed Complexity Sphere Decoder (SCSD), which executes the process of detection in MIMO systems with a significantly lower computation cost than the high-performance/reduced-complexity detectors: Sphere Decoder (SD), K-best, Fixed Complexity Sphere Decoder (FSD) and Adaptive Set Partitioning (ASP). Simulation results show that when the Signal-to-Noise Ratio (SNR) is less than 15dB, the SCSD reduces the complexity by up to 90% with respect to SD, up to 60% with respect to K-best or ASP and by up to 90% with respect to FSD. In the proposed algorithm, the BER performance does not show significant degradation and therefore, can be considered as a complexity reduction scheme suitable for implementing in MIMO detectors.

Interoperability is one of the fundamental functions of a home network because such networks must support many different types of devices and services. Interoperability can be realized by converting messages among different middleware with rules. However, it is very difficult to define common rules to accommodate all differences among various middleware. In addition, most interoperability approaches only address the conversion of the message format and schema, and occasionally these are not enough for a semantic conversion. In this paper, we propose a systematic approach to solve the interoperability problem. For this, we classify three interoperability types, i.e., schema, profile, and procedure, and define the rules for each type. We called this interoperability scheme the Multiple stage Approach for Home network Interoperability (MAHI). In this paper, we present the design and implementation of MAHI for a three-stage conversion process. Finally, we illustrate some experimental and quantitative results. In the experiments, MAHI can provide efficient interoperability among different middleware and MAHI will be a method to deal with a complex home network interoperability.

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.

A two-dimensional (2D) wireless power transmission (WPT) system that handles a wide range of transmitted and received power is proposed and evaluated. A transmitter outputs the power to an arbitrary position on a 2D waveguide sheet by using a beam-forming technique. The 2D waveguide sheet does not require an absorber on its edge. The minimum propagation power on the sheet is increased 18 times by using the beam-forming technique. Power amplifier (PA) efficiency was improved from 19% to 46% when the output power was 10dB smaller than peak power due to the use of a PA supply-voltage and input power control method. Peak PA efficiency was 60%. A receiver inputs a wide range of power levels and drives various load impedances with a parallel rectifier. This rectifier enables a number of rectifying units to be tuned dynamically. The rectifier efficiency was improved 1.5 times while input power range was expanded by 6dB and the load-impedance range was expanded fourfold. The rectifier efficiency was 66-73% over an input power range of 18-36dBm at load impedances of 100 and 400Ω.

In this paper, we consider distributed estimation where the measurement at each of the distributed sensor nodes is quantized before being transmitted to a fusion node which produces an estimate of the parameter of interest. Since each quantized measurement can be linked to a region where the parameter is found, aggregating the information obtained from multiple nodes corresponds to generating intersections between the regions. Thus, we develop estimation algorithms that seek to find the intersection region with the maximum likelihood rather than the parameter itself. Specifically, we propose two practical techniques that facilitate fast search with significantly reduced complexity and apply the proposed techniques to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our simulation results show that our proposed algorithms achieve good performance with reasonable complexity as compared with the minimum mean squared error (MMSE) and the maximum likelihood (ML) estimators.

This paper presents an adaptive feedback canceller (AFC) based on a pseudo affine projection (PAP) algorithm that can provide fast and stable adaptation to the time-varying environment. The proposed algorithm utilizes the adaptive linear prediction (LP) to obtain the LP coefficients of input signal model and the inverse gain filter (IGF) to alleviate the effect of compensation gain. As a result, when the input is model as an AR signal, the proposed algorithm satisfies the condition for having an almost unbiased estimatie of the feedback path and then its performance is relatively independent of the gain setting of hearing aids. Simulation results showed that the proposed algorithm is capable of obtaining unbaised feedback path estimates and high speech quality.