This paper presents novel structures of band-pass filters using two configurations of open loop ring resonators (OPLRR): a resonator with embedded quadruply-stepped impedance transmission lines (QSITL) in coupled lines, and a stepped impedance resonator (SIR). Both types of OPLRR have the capability of suppressing the second spurious response and shifting the third spurious response to a higher frequency as well. To demonstrate the performances of both proposed resonators, two sections of each structure with cascaded and crossed configurations at an operating frequency of 0.9 GHz are presented. Both methodologies are easy to design and implement. The methodology with a SIR has a better performance than the SITL. The measurement results of the proposed circuits are in full agreement with the simulated prediction results.

As a global feature of fingerprint patterns, the Orientation Field (OF) plays an important role in fingerprint recognition systems. This paper proposes a fast binary pattern based orientation estimation with nearest-neighbor search, which can reduce the computational complexity greatly. We also propose a classified post processing with adaptive averaging strategy to increase the accuracy of the estimated OF. Experimental results confirm that the proposed method can satisfy the strict requirements of the embedded applications over the conventional approaches.

A hybrid overlay/underlay spectrum sharing method for cognitive radio networks based on user classification and convex optimization is proposed. Interference radii are configured for the primary receiver and each cognitive receiver. Cognitive users are divided into four groups and allocated different spectrum sharing patterns according to their distance from the primary transmitter and receiver. An optimal power allocation scheme that achieves the maximum sum rate of cognitive radio system on the premise of satisfying the interference constraint of primary receiver is acquired through the convex optimization method. Performance analysis and simulation results show that, compared with existing methods, our method leads to improved performance of achievable sum rate of cognitive users while guarantees the transmission of primary users.

In this letter, a novel body bias selection scheme for minimizing the leakage of MOS transistors is presented. The proposed scheme directly monitors leakages at present and adjacent body bias voltages, and dynamically updates the voltage at which the leakage is minimized regardless of process and temperature variations. Comparison results in a 46 nm CMOS technology indicated that the proposed scheme achieved leakage reductions of up to 68% as compared to conventional body biasing schemes.

UWB (Ultra Wide-Band) pulse radar is promising for surveillance systems because it has an outstanding high range-resolution. To realize an accurate UWB radar imaging system, we propose a new approach that employs multipath echoes from a target in an indoor environment. Using multipath echoes, the proposed system can accurately estimate images, even for targets in a shadow region where the targets are out of sight of the antenna. We apply a simple interferometry technique using the multiple mirror image antennas generated by multipath propagation. We find that this simple method also produces many undesired false image points. To tackle this issue, we also propose an effective false image reduction algorithm to obtain a clear image. Numerical simulations verify that most of the false image points are removed and the target shape is accurately estimated.

The processor-sharing (PS) rule arises as a natural paradigm in a variety of practical situations, including time-shared computer systems. Although there has been much work on Poisson-input queueing analysis for the PS rule, there have been few results for renewal-input GI/G/1 (PS) systems. We consider the GI/G/1 (PS) system to provide develop a two-moment approximation for the mean performance measures. We derive the relationship between the mean unfinished work and the conditional mean sojourn time for the GI/G/1 (PS) system. Using this relationship, we derive approximate formulas for the mean conditional sojourn time, mean sojourn time, and the mean number of customers in the GI/G/1 (PS) system. Numerical examples are presented to compare the approximation with exact and simulated results. We show that the proposed approximate formulas have good accuracy.

In this letter, we focus on the spectrum sharing cognitive radio system, wherein a single-input multi-output cognitive fading channel is considered. Subject to the joint average interference constraint and peak interference constraint at the primary receiver, the outage capacity of the cognitive channel involving joint beamforming and power control is analyzed. We derive the optimal beamforming and power control strategy and deduce the closed-form expression for the outage capacity under Rayleigh fading model, the functional regions of two kinds of interference constraints are discussed as well. Furthermore, considering zero-outage transmission, we investigate the delay-limited capacity and introduce a new concept called the zero-outage average interference wall. Extensive simulations corroborate our theoretical results.

Locally linear embedding (LLE) is a well-known method for nonlinear dimensionality reduction. The mathematical proof and experimental results presented in this paper show that the neighborhood sizes in LLE must be smaller than the dimensions of input data spaces, otherwise LLE would degenerate from a nonlinear method for dimensionality reduction into a linear method for dimensionality reduction. Furthermore, when the neighborhood sizes are larger than the dimensions of input data spaces, the solutions to LLE are not unique. In these cases, the addition of some regularization method is often proposed. The experimental results presented in this paper show that the regularization method is not robust. Too large or too small regularization parameters cannot unwrap S-curve. Although a moderate regularization parameters can unwrap S-curve, the relative distance in the input data will be distorted in unwrapping. Therefore, in order to make LLE play fully its advantage in nonlinear dimensionality reduction and avoid multiple solutions happening, the best way is to make sure that the neighborhood sizes are smaller than the dimensions of input data spaces.

Change history in project revisions provides helpful information on handling bugs. Existing studies on predicting bugs mainly focus on resulting bug patterns, not these change patterns. When a code hunk is copied onto several files, the set of original and copied hunks often need to be consistently maintained. We assume that it is a normal state when all of hunks survive or die in a specific revision. When partial change occurs on some duplicated hunks, they are regarded as suspicious hunks. Based on these assumptions, suspicious cases can be predicted and the project's developers can be alerted. In this paper, we propose a practical approach to detect various change smells based on revision history and code hunk tracking. The change smells are suspicious change patterns that can result in potential bugs, such as partial death of hunks, missed refactoring or fix, backward or late change. To detect these change smells, three kinds of hunks – add, delete, and modify – are tracked and analyzed by an automated tool. Several visualized graphs for each type have been suggested to improve the applicability of the proposed technique. We also conducted experiments on large-scale open projects. The case study results show the applicability of the proposed approach.

In this letter, we propose a simple but effective buffer management scheme to achieve fair bandwidth sharing with a FIFO scheduling algorithm, that is, Dynamic Detection and Expulsion (DDE). The DDE scheme dynamically detects buffer occupancy and then precisely expels resided packets on demand through simple comparisons. Simulation results under various traffic conditions show that DDE can arrive at more robust and better fairness, and lower implementation complexity than that of a well-known Pushout (PO) scheme.

This work describes a 12-bit 100 MS/s 0.13 µm CMOS three-stage pipeline ADC with various circuit design techniques to reduce power and die area. Digitally controlled timing delay and gate-bootstrapping circuits improve the linearity and sampling time mismatch of the SHA-free input network composed of an MDAC and a FLASH ADC. A single two-stage switched op-amp is shared between adjacent MDACs without MOS series switches and memory effects by employing two separate NMOS input pairs based on slightly overlapped switching clocks. The interpolation, open-loop offset sampling, and two-step reference selection schemes for a back-end 6-bit flash ADC reduce both power consumption and chip area drastically compared to the conventional 6-bit flash ADCs. The prototype ADC in a 0.13 µm CMOS process demonstrates measured differential and integral non-linearities within 0.44LSB and 1.54LSB, respectively. The ADC shows a maximum SNDR and SFDR of 60.5 dB and 71.2 dB at 100 MS/s, respectively. The ADC with an active die area of 0.92 mm2 consumes 19 mW at 100 MS/s from a 1.0 V supply. The measured FOM is 0.22 pJ/conversion-step.

Per-flow traffic measurement is essential for network management; billing, traffic engineering, mitigating denial of service attacks, to mention just a few. In this field, the fundamental problem is that the size of expensive SRAM is too small to hold traffic data from high-speed networks. In this paper, we propose a new method for per-flow traffic measurement, which is based on the virtual vector that was originally designed for the problem of spread estimation. We modify the original virtual vector and show that this simple change yields a highly effective per-flow traffic estimator. Experiments show that our proposed scheme outperforms the state-of-the-art method in terms of both processing time and space requirement.

Wireless Sensor Networks (WSNs) are gradually moving toward the adoption of clustered heterogeneous designs, incorporating a mixture of variety kinds of sensor nodes with different radio coverage and battery capacity. Compared with homogeneous networks, heterogeneous networks are able to reduce the initial cost of the network or prolong the network lifetime. The architecture and routing protocol for this type of heterogeneous WSN should be energy aware in order to prolong the lifetime of the network. However, most of the existing clustering methods consider only initial energy of the sensor nodes and ignore the non-uniform energy drainage caused by many-to-one traffic near sink and/or cluster heads in heterogeneous network environment. In this paper, we propose a new clustering method for WSN with heterogeneous node types which selects cluster heads considering not only the transmission power and residual energy of each node but also those of its adjacent nodes. Simulation experiments show that the proposed method increases network lifetime by 80% and 60% more than that of the CC and HEED, respectively.

Many methods have been researched to prolong the lifetime of sensor networks that use mobile technologies. In the mobile sink research, there are the track based methods and the anchor points based methods as representative operation methods for mobile sinks. However, most existing methods decrease the Quality of Service (QoS) and lead to routing hotspots in the vicinity of the mobile sinks. The main reason is that they use static mobile sink movement paths that ignore the network environment such as the query position and the data priority. In this paper, we propose a novel mobile sink operation method that solves the problems of the existing methods. In our method, the probe priority of the mobile sink is determined from data priority to increase the QoS. The mobility of sink used to reduce the routing hotspot. Experiments show that the proposed method reduces the query response time and improves the network lifetime much more than the existing methods.

A bidirectional amplification module has been proposed for use in IP-over-CWDM networks. The module is based on a bidirectional erbium-doped fiber amplifier. The loss compensation characteristics of the module obtained in a bidirectional IP transmission experiment confirmed that the losses of the optical node and the transmission fiber in the network can be compensated for effectively by the module making it possible to increase the number of nodes and the total fiber length of the network.

Existing filtering methods of TCP ACK packets are known to be effective in reducing the required bandwidth, resulting in the improvement of TCP throughput. However, the methods cannot handle the filtering of piggyback ACK packets. Considering that most TCP applications require bidirectional data exchange, the lack of the functionality to deal with the piggyback ACK packets should be addressed. This paper proposes a novel filtering scheme for WiMAX systems that can handle the piggyback ACK packets. The novelty comes from the fact that the proposed method overlaps the processing time of packet merging with the round trip delay of the bandwidth request-and-grant procedure. It is advantageous because it does not require extra time for the merging. The results from an analytical model and simulations show that the required uplink bandwidth is decreased while the downlink throughput is increased.

The detection of object categories with large variations in appearance is a fundamental problem in computer vision. The appearance of object categories can change due to intra-class variations, background clutter, and changes in viewpoint and illumination. For object categories with large appearance changes, some kind of sub-categorization based approach is necessary. This paper proposes a sub-category optimization approach that automatically divides an object category into an appropriate number of sub-categories based on appearance variations. Instead of using predefined intra-category sub-categorization based on domain knowledge or validation datasets, we divide the sample space by unsupervised clustering using discriminative image features. We then use a cluster performance analysis (CPA) algorithm to verify the performance of the unsupervised approach. The CPA algorithm uses two performance metrics to determine the optimal number of sub-categories per object category. Furthermore, we employ the optimal sub-category representation as the basis and a supervised multi-category detection system with χ2 merging kernel function to efficiently detect and localize object categories within an image. Extensive experimental results are shown using a standard and the authors' own databases. The comparison results reveal that our approach outperforms the state-of-the-art methods.

It is an important problem to determine major collection times to meet the pause time goal for a generational garbage collector. From such a viewpoint, this paper proposes two stochastic models based on working schemes of a generational garbage collector: Garbage collections occur in a nonhomogeneous Poisson process, tenuring collection is made at a threshold level K, and major collection is made at time T or at Nth collection including minor and tenuring collections for the first model and at time T or at Nth collection including tenuring collections for the second model. Using the techniques of cumulative processes and reliability theory, expected cost rates are obtained, and optimal policies of major collection times which minimize them are discussed analytically and computed numerically.

This paper studies the design of Cascade Granular Neural Networks (CGNN) for human-centric systems. In contrast to typical rule-based systems encountered in fuzzy modeling, the proposed method consists of two-phase development for CGNN. First, we construct a Granular Neural Network (GNN) which could be treated as a preliminary design. Next, all modeling discrepancies are compensated by a second GNN with a collection of rules that become attached to the regions of the input space where the error is localized. These granular networks are constructed by building a collection of user-centric information granules through Context-based Fuzzy c-Means (CFCM) clustering. Finally, the experimental results on two examples reveal that the proposed approach shows good performance in comparison with the previous works.

Verifying the signing order is sometimes very important in multisignature schemes. A multisignature scheme in which the signing order can be verified is called structured multisignature scheme and many such schemes have been proposed so far. However, there are not many structured multisignature schemes utilizing an algebraic structure of underlying algebraic operation. Ohmori, Chida, Shizuya and Nishizeki have proposed a structured multisignature scheme by utilizing a non-commutative ring homomorphism. Since their scheme does not fully reflect the structure of signers and its rigorous security analysis is not provided, we construct an improved structured multisignature scheme overcoming these problems by utilizing the non-commutative ring homomorphism in a different way and discuss its rigorous security against various attacks, including signer structure forgery, rogue key attack and attack-0 under the discrete logarithm assumption. As far as we know, the scheme in [30], which does not use non-commutative ring homomorphism, guarantees the most rigorous security but the number of signers is restricted in order to prevent attack-0. In contrast, our scheme overcomes attack-0 by virtue of a ring homomorphism and no restriction is imposed on the number of signers.