Recent idea visualization programs still lack automatic idea summarization capabilities. This paper presents a knowledge-based method for automatically providing a short piece of English text about a topic to each idea group in idea charts. This automatic topic identification makes used Yet Another General Ontology (YAGO) and Wordnet as its knowledge bases. We propose a novel topic selection method and we compared its performance with three existing methods using two experimental datasets constructed using two idea visualization programs, i.e., the KJ Method (Kawakita Jiro Method) and mind-mapping programs. Our proposed topic identification method outperformed the baseline method in terms of both performance and consistency.

In this letter, the problem of feature quantization in robust hashing is studied from the perspective of approximate nearest neighbor (ANN). We model the features of perceptually identical media as ANNs in the feature set and show that ANN indexing can well meet the robustness and discrimination requirements of feature quantization. A feature quantization algorithm is then developed by exploiting the random-projection based ANN indexing. For performance study, the distortion tolerance and randomness of the quantizer are analytically derived. Experimental results demonstrate that the proposed work is superior to state-of-the-art quantizers, and its random nature can provide robust hashing with security against hash forgery.

In large-scale collaborative computing, users and resource providers organize various Virtual Organizations (VOs) to share resources and services. A VO organizes other sub-VOs for the purpose of achieving the VO goal, which forms hierarchical VO environments. VO participants agree upon a certain policies, such as resource sharing amount or user accesses. In this letter, we provide an optimal resource sharing mechanism in hierarchical VO environments under resource sharing agreements. The proposed algorithm enhances resource utilization and reduces mean response time of each user.

Granular gain of low-dimensional lattices based on binary linear codes is estimated using a quantization algorithm which is equivalently a soft-decision decoding of the underlying code. It is shown that substantial portion of the ultimate granular gain is achieved even in limited dimensions.

In this paper, a new systolic array structure for the extended QR decomposition based recursive least-square (QRD-RLS) equalizer is proposed. The fact that the vectoring and rotation mode coordinate rotation digital computer (CORDIC) processors rotate in the same direction is used to show that the hardware complexity of the systolic array can be reduced. Furthermore, since the vectoring and rotation mode CORDIC processors in the proposed structure rotate simultaneously, operation time is also reduced. The performance of the proposed equalizer is analyzed by observing the flatness obtained by multiplying the frequency responses of the unknown channel with the proposed equalizer. Simulation results through hardware description language (HDL) coding and synthesis show that 23.8% of the chip implementation area can be reduced.

We propose an optimization method for power distribution network that explicitly deals with timing. We have found and focused on the facts that decoupling capacitance (decap) does not necessarily improve gate delay depending on the switching timing within a cycle and that power wire expansion may locally degrade the voltage. To resolve the above facts, we devised an efficient sensitivity calculation of timing to decap size and power wire width for guiding optimization. The proposed method, which is based on statistical noise modeling and timing analysis, accelerates sensitivity calculation with an approximation and adjoint sensitivity analysis. Experimental results show that decap allocation based on the sensitivity analysis efficiently minimizes the worst-case circuit delay within a given decap budget. Compared to the maximum decap placement, the delay improvement due to decap increases by 3.13% even while the total amount of decaps is reduced to 40%. The wire sizing with the proposed method also efficiently reduces required wire resource necessary to attain the same circuit delay by 11.5%.

An accurate and rapid synchronization scheme is a prerequisite for achieving high-quality multimedia transmission for wireless handheld terminals, e.g. China multimedia mobile broadcasting (CMMB) system. In this paper, an efficient orthogonal frequency division multiplexing (OFDM) timing synchronization scheme, which is robust to the doubly selective fading channel, is proposed for CMMB system. TS timing is derived by performing an inverse sliding correlation (ISC) between the segmented Sync sequences in the Beacon, which possesses the inverse conjugate symmetry (ICS) characteristic. The ISC can provide sufficient correlative gain even in the ultra low signal noise ratio (SNR) scenarios. Moreover, a fast fine symbol timing method based on the auto-correlation property of Sync sequence is also presented. According to the detection strategy for the significant channel taps, the specific information about channel profile can be obtained. The advantages of the proposed timing scheme over the traditional ones have been demonstrated through both theoretical analysis and numerical simulations.

This paper proposes a spectrum-overlapped resource management (SORM) technique where each user equipment (UE) can ideally obtain the frequency selection diversity gain under multi-user environments. In the SORM technique for cellular systems, under assumption of adopting a soft canceller with minimum mean square error (SC/MMSE) turbo equalizer, an evolved node B (eNB) accepts overlapped frequency resource allocation. As a result, each UE can use the frequency bins having the highest channel gain. However, the SORM becomes non-orthogonal access when the frequency bins having high channel gain for UEs are partially identical. In this case, the inter-user interference (IUI) caused by overlapping spectra among UEs is eventually canceled out by using the SC/MMSE turbo equalizer. Therefore, SORM can achieve better performance than orthogonal access e.g. FDMA when the IUI is completely canceled. This paper demonstrates that SORM has the potential to improve transmission performance, by extrinsic information transfer (EXIT) analysis. Moreover, this paper evaluates the block error rate (BLER) performance of the SORM and the FDMA. Consequently, this paper shows that the SORM outperforms the FDMA.

Random telegraph noise (RTN) is a phenomenon that is considered to limit the reliability and performance of circuits using advanced devices. The time constants of carrier capture and emission and the associated change in the threshold voltage are important parameters commonly included in various models, but their extraction from time-domain observations has been a difficult task. In this study, we propose a statistical method for simultaneously estimating interrelated parameters: the time constants and magnitude of the threshold voltage shift. Our method is based on a graphical network representation, and the parameters are estimated using the Markov chain Monte Carlo method. Experimental application of the proposed method to synthetic and measured time-domain RTN signals was successful. The proposed method can handle interrelated parameters of multiple traps and thereby contributes to the construction of more accurate RTN models.

This paper evaluates the impact of Through-Silicon Via (TSV) on the performance and power consumption of 3D circuitry. The physical and electrical model of TSV which considers the coupling effects with adjacent TSVs is exploited in our investigation. Simulation results show that the overall performance of 3D IC infused with TSV can be improved noticeably. The frequency of the ring oscillator in 4-tier stacking layout soars up to two times compared with one in 2D planar. Furthermore, TSV process variations are examined by Monte Carlo simulations to figure out the geometrical factor having more impact in manufacturing. An in-depth research on repeater associated with TSV offers a metric to compute the optimization of 3D systems integration in terms of performance and energy dissipation. By such optimization metric with 45 nm MOSFET used in our circuit layout, it is found that the optimal number of tiers in both performance and power consumption approaches 4 since the substantial TSV-TSV coupling effect in the worst case of interference is expected in 3D IC.

Based on a proposed frame structure with an unequal sensing slot duration for each channel, and two sensing scenarios (with or without cooperation), a joint channel and sensing time assignment is suggested to maximize the uplink throughput of the centralized multi-band cognitive radio network with the consideration of the mutual interference among the secondary users (SUs). Firstly, the channel assignment is performed by using the proposed Delta Non-square Hungarian (DNH), which is a modified iterative Hungarian algorithm distinguished by throughput increment maximization and non-square weight matrix. Simulation results illustrate that DNH has significant advantages in enhancing the throughput and reducing the computational complexity. Moreover, a hybrid channel assignment, also performed by DNH, is improved based on the two sensing scenarios to maximize the throughput while efficiently limiting the interference power to primary users. Secondly, the convexity of the throughput functions within the range of sensing time is proved under the proposed frame structure, and then the maximum throughput is achieved through the steepest descent method-based sensing time assignment. Both of these results are corroborated by simulations.

Yield-driven clock skew scheduling was previously formulated as a minimum cost-to-time ratio cycle problem, by assuming that variational path delays are in Gaussian distributions. However in today's nanometer technology, process variations show growing impacts on this assumption, as variational delays with non-Gaussian distributions have been observed on these paths. In this paper, we propose a novel yield-driven clock skew scheduling method for arbitrary distributions of critical path delays. Firstly, a general problem formulation is proposed. By integrating the cumulative distribution function (CDF) of critical path delays, the formulation is able to handle path delays with any distributions. It also generalizes the previous formulations on yield-driven clock skew scheduling and indicates their statistical interpretations. Generalized Howard algorithm is derived for finding the critical cycles of the underlying timing constraint graphs. Moreover, an effective algorithm based on minimum balancing is proposed for the overall yield improvement. Experimental results on ISCAS89 benchmarks show that, compared with two representative existing methods, our method remarkably improves the yield by 10.25% on average (up to 14.66%).

We investigate a design strategy for subthreshold circuits focusing on energy-consumption minimization and yield maximization under process variations. The design strategy is based on the following findings related to the operation of low-power CMOS circuits: (1) The minimum operation voltage (VDDmin) of a circuit is dominated by flip-flops (FFs), and VDDmin of an FF can be improved by upsizing a few key transistors, (2) VDDmin of an FF is stochastically modeled by a log-normal distribution, (3) VDDmin of a large circuit can be efficiently estimated by using the above model, which eliminates extensive Monte Carlo simulations, and (4) improving VDDmin may substantially contribute to decreasing energy consumption. The effectiveness of the proposed design strategy has been verified through circuit simulations on various circuits, which clearly show the design tradeoff between voltage scaling and transistor sizing.

Many learning machines such as normal mixtures and layered neural networks are not regular but singular statistical models, because the map from a parameter to a probability distribution is not one-to-one. The conventional statistical asymptotic theory can not be applied to such learning machines because the likelihood function can not be approximated by any normal distribution. Recently, new statistical theory has been established based on algebraic geometry and it was clarified that the generalization and training errors are determined by two birational invariants, the real log canonical threshold and the singular fluctuation. However, their concrete values are left unknown. In the present paper, we propose a new concept, a quasi-regular case in statistical learning theory. A quasi-regular case is not a regular case but a singular case, however, it has the same property as a regular case. In fact, we prove that, in a quasi-regular case, two birational invariants are equal to each other, resulting that the symmetry of the generalization and training errors holds. Moreover, the concrete values of two birational invariants are explicitly obtained, hence the quasi-regular case is useful to study statistical learning theory.

This paper investigates the dominant impact on the interference rejection combining (IRC) receiver due to the downlink reference signal (RS) based covariance matrix estimation scheme. When the transmission modes using the cell-specific RS (CRS) in LTE/LTE-Advanced are assumed, the property of the non-precoded CRS is different from that of the data signals. This difference poses two problems to the IRC receiver. First, it results in different levels of accuracy for the RS based covariance matrix estimation. Second, assuming the case where the CRS from the interfering cell collides with the desired data signals of the serving cell, the IRC receiver cannot perfectly suppress this CRS interference. The results of simulations assuming two transmitter and receiver antenna branches show that the impact of the CRS-to-CRS collision among cells is greater than that for the CRS interference on the desired data signals especially in closed-loop multiple-input multiple-output (MIMO) systems, from the viewpoint of the output signal-to-interference-plus-noise power ratio (SINR). However, the IRC receiver improves the user throughput by more than 20% compared to the conventional maximal ratio combining (MRC) receiver under the simulation assumptions made in this paper even when the CRS-to-CRS collision is assumed. Furthermore, the results verify the observations made in regard to the impact of inter-cell interference of the CRS for various average received signal-to-noise power ratio (SNR) and signal-to-interference power ratio (SIR) environments.

In this paper, we propose a virtualization architecture for a multi-core embedded system to provide more system reliability and security while maintaining performance and without introducing additional special hardware supports or implementing a complex protection mechanism in the virtualization layer. Embedded systems, especially consumer electronics, have often used virtualization. Virtualization is not a new technique, as there are various uses for both GPOS (General Purpose Operating System) and RTOS (Real Time Operating System). The surge of the multi-core platforms in embedded systems also helps consolidate the virtualization system for better performance and lower power consumption. Embedded virtualization design usually uses two approaches. The first is to use the traditional VMM, but it is too complicated for use in the embedded environment without additional special hardware support. The other approach uses the microkernel, which imposes a modular design. The guest systems, however, would suffer from considerable modifications in this approach, as the microkernel allows guest systems to run in the user space. For some RTOSes and their applications originally running in the kernel space, this second approach is more difficult to use because those codes use many privileged instructions. To achieve better reliability and keep the virtualization layer design lightweight, this work uses a common hardware component adopted in multi-core embedded processors. In most embedded platforms, vendors provide additional on-chip local memory for each physical core, and these local memory areas are only private to their cores. By taking advantage of this memory architecture, we can mitigate the above-mentioned problems at once. We choose to re-map the virtualization layer's program on the local memory, called SPUMONE, which runs all guest systems in the kernel space. Doing so, it can provide additional reliability and security for the entire system because the SPUMONE design in a multi-core platform has each instance installed on a separate processor core. This design differs from traditional virtualization layer design, and the content of each SPUMONE is inaccessible to the others. We also achieve this goal without adding overhead to the overall performance.

This letter presents a flexible signal structure supporting localization service for time domain synchronous OFDM (TDS-OFDM) in multi-service transmission applications. Localization is treated as one specific service and the corresponding data is allocated within the physical layer pipe (PLP) of the first subframe. The concept of variable sub-carrier spacing to combat Doppler spread is also introduced for the localization service. Simulation results indicate that the proposed scheme outperforms the conventional scheme and at the same time achieves high positioning accuracy.

In this letter, the tradeoff between symbol rate and diversity gain of Space-Time Block Codes (STBCs) with linear receivers is considered. It is known that Group Orthogonal-Toeplitz Codes (GOTCs) can achieve a good tradeoff with linear receivers. However, the symbol rate of GOTCs is limited to that of the base Orthogonal Space-Time Block Codes (OSTBCs). We propose to simply change the GOTC base codes from OSTBCs to Quasi-Orthogonal Space-Time Block Codes (Q-OSTBCs). Q-OSTBCs can improve the symbol rate of GOTCs at the expense of diversity gain. Simulation results show that Q-OSTBC based GOTCs can improve the tradeoff between symbol rate and diversity gain over that of the original GOTCs.

In order to reduce cost and improve efficiency, many data centers adopt virtualization solutions. The advent of virtualization allows multiple virtual machines hosted on a single physical server. However, this poses new challenges for resource management. Web workloads which are dominant in data centers are known to vary dynamically with time. In order to meet application's service level agreement (SLA), how to allocate resources for virtual machines has become an important challenge in virtualized server environments, especially when dealing with fluctuating workloads and complex server applications. User experience is an important manifestation of SLA and attracts more attention. In this paper, the SLA is defined by server-side response time. Traditional resource allocation based on resource utilization has some drawbacks. We argue that dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines response time measurements and analysis of user experience for resource allocation. An optimization model is introduced to dynamically allocate the resources among virtual machines. When resources are insufficient, we provide service differentiation and firstly guarantee resource requirements of applications that have higher priorities. We evaluate our proposal using TPC-W and Webbench. The experimental results show that our system can judiciously allocate system resources. The system helps stabilize applications' user experience. It can reduce the mean deviation of user experience from desired targets.

In content services where people purchase and download large-volume contents, minimizing network traffic is crucial for the service provider and the network operator since they want to lower the cost charged for bandwidth and the cost for network infrastructure, respectively. Traffic localization is an effective way of reducing network traffic. Network traffic is localized when a client can obtain the requested content files from other a near-by altruistic client instead of the source servers. The concept of the peer-assisted content distribution network (CDN) can reduce the overall traffic with this mechanism and enable service providers to minimize traffic without deploying or borrowing distributed storage. To localize traffic effectively, content files that are likely to be requested by many clients should be cached locally. This paper presents a novel traffic engineering scheme for peer-assisted CDN models. Its key idea is to control the behavior of clients by using content-oriented incentive mechanism. This approach enables us to optimize traffic flows by letting altruistic clients download content files that are most likely contributed to localizing traffic among clients. In order to let altruistic clients request the desired files, we combine content files while keeping the price equal to the one for a single content. This paper presents a solution for optimizing the selection of content files to be combined so that cross traffic in a network is minimized. We also give a model for analyzing the upper-bound performance and the numerical results.