Information security has been seriously threatened by the differential power analysis (DPA). Delay-based dual-rail precharge logic (DDPL) is an effective solution to resist these attacks. However, conventional DDPL convertors have some shortcomings. In this paper, we propose improved convertor pairs based on dynamic logic and a sense amplifier (SA). Compared with the reference CMOS-to-DDPL convertor, our scheme could save 69% power consumption. As to the comparison of DDPL-to-CMOS convertor, the speed and power performances could be improved by 39% and 54%, respectively.

This paper presents a novel data compression method for testing integrated circuits within the framework of pattern run-length coding. The test set is firstly divided into 2n-length patterns where n is a natural number. Then the compatibility of each pattern, which can be an external type, or an internal type, is analyzed. At last, the codeword of each pattern is generated according to its analysis result. Experimental results for large ISCAS89 benchmarks show that the proposed method can obtain a higher compression ratio than existing ones.

This paper proposes the use of on-chip monitor circuits to detect process shift and process spread for post-silicon diagnosis and model-hardware correlation. The amounts of shift and spread allow test engineers to decide the correct test strategy. Monitor structures suitable for detection of process shift and process spread are discussed. Test chips targeting a nominal process corner as well as 4 other corners of “slow-slow”, “fast-fast”, “slow-fast” and “fast-slow” are fabricated in a 65nm process. The monitor structures correctly detects the location of each chip in the process space. The outputs of the monitor structures are further analyzed and decomposed into the process variations in threshold voltage and gate length for model-hardware correlation. Path delay predictions match closely with the silicon values using the extracted parameter shifts. On-chip monitors capable of detecting process shift and process spread are helpful for performance prediction of digital and analog circuits, adaptive delay testing and post-silicon statistical analysis.

The computing of applications in embedded devices suffers tight constraints on computation and energy resources. Thus, it is important that applications running on these resource-constrained devices are aware of the energy constraint and are able to execute efficiently. The existing execution time and energy profiling tools could help developers to identify the bottlenecks of applications. However, the profiling tools need large space to store detailed profiling data at runtime, which is a hard demand upon embedded devices. In this article, a reconfigurable multi-resolution profiling (RMP) approach is proposed to handle this issue on embedded devices. It first instruments all profiling points into source code of the target application and framework. Developers can narrow down the causes of bottleneck by adjusting the profiling scope using the configuration tool step by step without recompiling the profiled targets. RMP has been implemented as an open source tool on Android systems. Experiment results show that the required log space using RMP for a web browser application is 25 times smaller than that of Android debug class, and the profiling error rate of execution time is proven 24 times lower than that of debug class. Besides, the CPU and memory overheads of RMP are only 5% and 6.53% for the browsing scenario, respectively.

In this paper we propose a novel method to reduce power consumption during scan testing caused by test responses at scan-out operation for logic BIST. The proposed method overwrites some flip-flops (FFs) values before starting scan-shift so as to reduce the switching activity at scan-out operation. In order to relax the fault coverage loss caused by filling new FF values before observing the capture values at the FFs, the method employs multi-cycle scan test with partial observation. For deriving larger scan-out power reduction with less fault coverage loss and preventing hardware overhead increase, the FFs to be filled are selected in a predetermined ratio. For overwriting values, we prepare three value filling methods so as to achieve larger scan-out power reduction. Experiment for ITC99 benchmark circuits shows the effectiveness of the methods. Nearly 51% reduction of scan-out power and 57% reduction of peak scan-out power are achieved with little fault coverage loss for 20% FFs selection, while hardware overhead is little that only 0.05%.

Current network elements consume 10-20% of the total power in data centers. Today's network elements are not energy-proportional and consume a constant amount of energy regardless of the amount of traffic. Thus, turning off unused network switches is the most efficient way of reducing the energy consumption of data center networks. This paper presents Honeyguide, an energy optimizer for data center networks that not only turns off inactive switches but also increases the number of inactive switches for better energy-efficiency. To this end, Honeyguide combines two techniques: 1) virtual machine (VM) and traffic consolidation, and 2) a slight extension to the existing tree-based topologies. Honeyguide has the following advantages. The VM consolidation, which is gracefully combined with traffic consolidation, can handle severe requirements on fault tolerance. It can be introduced into existing data centers without replacing the already-deployed tree-based topologies. Our simulation results demonstrate that Honeyguide can reduce the energy consumption of network elements better than the conventional VM migration schemes, and the savings are up to 7.8% in a fat tree with k=12.

In this paper, we present an approach for 3D face recognition based on Multi-level Partition of Unity (MPU) Implicits under pose and expression variations. The MPU Implicits are used for reconstructing 3D face surface in a hierarchical way. Three landmarks, nose, left eyehole and right eyehole, can be automatically detected with the analysis of curvature features at lower levels of reconstruted face. Thus, the 3D faces are initially registered to a common coordinate system based on the three landmarks. A variant of Iterative Closest Point (ICP) algorithm is proposed for matching the point surface of a given probe face to the implicits face surface in the gallery. To evaluate the performance of our approach for 3D face recognition, we perform an experiment on GavabDB face database. The results of the experiment show that our method based on MPU Implicits and Adaptive ICP has great capability for 3D face recognition under pose and expression variations.

We propose a novel method for knowledge consolidation based on a knowledge graph as a next step in relation extraction from text. The knowledge consolidation method consists of entity consolidation and relation consolidation. During the entity consolidation process, identical entities are found and merged using both name similarity and relation similarity measures. In the relation consolidation process, incorrect relations are removed using cardinality properties, temporal information and relation weight in given graph structure. In our experiment, we could generate compact and clean knowledge graphs where number of entities and relations are reduced by 6.1% and by 17.4% respectively with increasing relation accuracy from 77.0% to 85.5%.

This paper proposes an enhancement to a previously reported adaptive peak-to-average power ratio (PAPR) reduction method based on clipping and filtering (CF) for eigenmode multiple-input multiple-output (MIMO) — orthogonal frequency division multiplexing (OFDM) signals. We enhance the method to accommodate the case with adaptive modulation and channel coding (AMC). Since the PAPR reduction process degrades the signal-to-interference and noise power ratio (SINR), the AMC should take into account this degradation before PAPR reduction to select accurately the modulation scheme and coding rate (MCS) for each spatial stream. We use the lookup table-based prediction of SINR after PAPR reduction, in which the interference caused by the PAPR reduction is obtained as a function of the stream index, frequency block index, clipping threshold for PAPR reduction, and input backoff (IBO) of the power amplifier. Simulation results show that the proposed PAPR reduction method increases the average throughput compared to the conventional CF method for a given adjacent channel leakage power ratio (ACLR) when we assume practical AMC.

We propose a current mode sense amplifier that uses a current-mirror to increase the bitline sensing current, which dominates the sensing speed. A comparison of the sensing delay shows that the proposed sense amplifier can provide about 12.6∼15.4% improvement depending on different bitline loads in sensing speed over original WTA scheme.

Bridge-type contacts are mainly used in high voltage direct current contactors for their performance of arc extinguishment and break capacity. It is also easy to add external magnetic field in them to blow the arc. Experiments on the arc behaviors were carried out when a copper bridge-type contact pair opening a 270V resistive circuit in the air. Influences of the shape of the movable contact, the opening speed and the magnetic flux density on the key behaviors, such as the arc duration, the arc re-ignition and the stability of arcing process, were investigated by using an oscilloscope and a high-speed camera. It was revealed that a uniform magnetic field with proper density could extinguish the arc stably and could reduce the arc re-ignition.

Large-scale disasters may cause simultaneous failures of many components in information systems. In the design for disaster recovery, operational procedures to recover from simultaneous component failures need to be determined so as to satisfy the time-to-recovery objective within the limited budget. For this purpose, it is beneficial to identify the smallest unacceptable combination of component failures (SUCCF) which exceeds the acceptable cost for recovering the system. This allows us to know the limitation of the recovery capability of the designed recovery operation procedure. In this paper, we propose a technique to identify the SUCCF by predicting the required cost for recovery from each combination of component failures with and without two-person cross-check of execution of recovery operations. We synthesize analytic models from the description of recovery operation procedure in the form of SysML Activity Diagram, and solve the models to predict the time-to-recovery and the cost. An example recovery operation procedure for a commercial database management system is used to demonstrate the proposed technique.

We propose a low-overhead fault-secure parallel prefix adder. We duplicate carry bits for checking purposes. Only one half of normal carry bits are compared with the corresponding redundant carry bits, and the hardware overhead of the adder is low. For concurrent error detection, we also predict the parity of the result. The adder uses parity-based error detection and it has high compatibility with systems that have parity-based error detection. We can implement various fault-secure parallel prefix adders such as Sklansky adder, Brent-Kung adder, Han-Carlson adder, and Kogge-Stone adder. The area overhead of the proposed adder is about 15% lower than that of a previously proposed adder that compares all the carry bits.

Hyperthermia is one of the modalities for cancer treatment, utilizing the difference of thermal sensitivity between tumor and normal tissue. Interstitial microwave hyperthermia is one of the heating schemes and it is applied to a localized tumor. In the treatments, heating pattern control around antennas are important, especially for the treatment in and around critical organs. This paper introduces a coaxial-dipole antenna, which is one of the thin microwave antennas and can generate a controllable heating pattern. Moreover, generations of an arbitrary shape heating patterns by an array applicator composed of four coaxial-dipole antennas are described.

This study extends conventional fingerprint recognition from a supervised to an unsupervised framework. Instead of enrolling fingerprints from known persons to identify unknown fingerprints, our aim is to partition a collection of unknown fingerprints into clusters, so that each cluster consists of fingerprints from the same finger and the number of generated clusters equals the number of distinct fingers involved in the collection. Such an unsupervised framework is helpful to handle the situation where a collection of captured fingerprints are not from the enrolled people. The task of fingerprint clustering is formulated as a problem of minimizing the clustering errors characterized by the Rand index. We estimate the Rand index by computing the similarities between fingerprints and then apply a genetic algorithm to minimize the Rand index. Experiments conducted using the FVC2002 database show that the proposed fingerprint clustering method outperforms an intuitive method based on hierarchical agglomerative clustering. The experiments also show that the number of clusters determined by our system is close to the true number of distinct fingers involved in the collection.

In this letter, an adaptive detection scheme for a multiple-input multiple-output (MIMO) system is proposed. In order to reduce the complexity of the decoding steps, the initial symbol is obtained by a MMSE equalizer and then the symbol ordering is performed by the channel state. After the received symbols are divided according to the channel state, some of the symbols are detected by using the MMSE detector with low complexity. With cancelation processing, the remainder symbols are detected for the K-best detector. The proposed adaptive detection scheme combines the MMSE and K-best detector based on the channel state. Therefore, the proposed adaptive detector achieves a good performance.

Based on sample-pair refinement and local optimization, this paper proposes a high-accuracy and quick matting algorithm. First, in order to gather foreground/background samples effectively, we shoot rays in hybrid (gradient and uniform) directions. This strategy utilizes the prior knowledge to adjust the directions for effective searching. Second, we refine sample-pairs of pixels by taking into account neighbors'. Both high confidence sample-pairs and usable foreground/background components are utilized and thus more accurate and smoother matting results are achieved. Third, to reduce the computational cost of sample-pair selection in coarse matting, this paper proposes an adaptive sample clustering approach. Most redundant samples are eliminated adaptively, where the computational cost decreases significantly. Finally, we convert fine matting into a de-noising problem, which is optimized by minimizing the observation and state errors iteratively and locally. This leads to less space and time complexity compared with global optimization. Experiments demonstrate that we outperform other state-of-the-art methods in local matting both on accuracy and efficiency.

We experimentally investigate and analyze faults in optical fiber connections with refractive index matching material that have incorrectly cleaved fiber ends. We explain that incorrectly cleaved fiber ends, which are not ideal because they are uneven and not perpendicular to the fiber axis, are caused by defective optical fiber cleavers. We discover that the optical performance of field installable connections using incorrectly cleaved fiber ends might change greatly. We also infer that the significant change in insertion and return losses might be attributed to partially air-filled gaps by using scatter diagrams of measured insertion and return losses. Our experiment results reveal that the optical performance might deteriorate to more than 40dB in terms of insertion loss and less than 30dB in terms of return loss.

As a network evolves following initial deployment, its service functions remain diversified through the openness of the network functions. This indicates that appropriate simplification of the service functions is essential if the evolving network is to achieve the required scalability of service processing and service management. While the screening of service functions is basically performed by network users and the market, several service functions will be automatically simplified based on the growth of the evolving network. This paper verifies the simplification of service functions resulting from the evolution of the network itself. First, the principles that serve as the basis for simplifying the service functions are explained using several practical examples. Next, a simulation model is proposed to verify the simplification of service functions in terms of the priority control function for path routing and load balancing among multiple paths. From the results of the simulation, this study clarifies that the anticipated simplification of service functions is actually realizable and the service performance requirements can be reduced as the network evolves after deployment. When the simplification of service functions can improve network quality, it accelerates the evolution of the network and increases the operator's revenue.