This paper proposes a novel method for adaptively controlling the admission of interference to users in our previously proposed layered partially non-orthogonal block diagonalization (BD) precoding method for downlink multiuser multiple-input multiple-output (MIMO) transmission that employs cooperation among multiple base stations (BSs). The proposed method is applicable when some of the instantaneous channel state information (CSI) feedback between the user equipment and the respective BSs is missing if the path loss between the user equipment and BS is higher than a predetermined threshold. The proposed method suppresses the loss in the transmitter diversity (beam forming) gain caused by the perfect nulling of inter-user interference in BD. By allowing the inter-user interference from a link that has a high average path loss, the overall throughput performance of simple BD is enhanced. We show that the combination of layered transmission that restricts the set of BSs used for the signal transmission and adaptive control of interference admission significantly increases the throughput of BS cooperative multiuser MIMO with partial CSI feedback.

In signal restoration problems, we expect to improve the restoration performance with a priori information about unknown target signals. In this paper, the parametric Wiener filter with linear constraints for unknown target signals is discussed. Since the parametric Wiener filter is usually defined as the minimizer of the criterion not for the unknown target signal but for the filter, it is difficult to impose constraints for the unknown target signal in the criterion. To overcome this difficulty, we introduce a criterion for the parametric Wiener filter defined for the unknown target signal whose minimizer is equivalent to the solution obtained by the original formulation. On the basis of the newly obtained criterion, we derive a closed-form solution for the parametric Wiener filter with linear constraints.

In this letter, constructions of sequences with perfect odd autocorrelation and sequence sets with zero odd correlation zone (ZOCZ) over the 8-QAM+ constellation are presented. Based on odd perfect ternary sequences, odd perfect sequences and ZOCZ sequence sets over the 8-QAM+ constellation are constructed by using shift vectors and mappings. These odd perfect sequences and ZOCZ sequence sets over 8-QAM+ constellation can be used in communication systems to achieve high transmission data rate (TDR) and low interference.

A macroscopic structure was analyzed for a system comprising multiple elements in which the dynamics is affected by their distribution. First, a nonlinear Boltzmann equation, which has an integration term with respect to the distribution of the elements, was derived. Next, the moment vector equation (MVE) for the Boltzmann equation was derived. The average probability density function (pdf) in a steady state was derived using eigen analysis of the coefficient matrix of the MVE. The macroscopic structure of the system and the mechanism that provides the average pdf and the transient response were then analyzed using eigen analysis. Evaluation of the average pdf and transient response showed that using eigen analysis is effective for analyzing not only the transient and stationary properties of the system but also the macroscopic structure and the mechanism providing the properties.

Recently, fuzzy set theory has been widely employed in building portfolio selection models where uncertainty plays a role. In these models, future security returns are generally taken for fuzzy variables and mathematical models are then built to maximize the investment profit according to a given risk level or to minimize a risk level based on a fixed profit level. Based on existing works, this paper proposes a portfolio selection model based on fuzzy birandom variables. Two original contributions are provided by the study: First, the concept of technical analysis is combined with fuzzy set theory to use the security returns as fuzzy birandom variables. Second, the fuzzy birandom Value-at-Risk (VaR) is used to build our model, which is called the fuzzy birandom VaR-based portfolio selection model (FBVaR-PSM). The VaR can directly reflect the largest loss of a selected case at a given confidence level and it is more sensitive than other models and more acceptable for general investors than conventional risk measurements. To solve the FBVaR-PSM, in some special cases when the security returns are taken for trapezoidal, triangular or Gaussian fuzzy birandom variables, several crisp equivalent models of the FBVaR-PSM are derived, which can be handled by any linear programming solver. In general, the fuzzy birandom simulation-based particle swarm optimization algorithm (FBS-PSO) is designed to find the approximate optimal solution. To illustrate the proposed model and the behavior of the FBS-PSO, two numerical examples are introduced based on investors' different risk attitudes. Finally, we analyze the experimental results and provide a discussion of some existing approaches.

As businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highly-available resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). Subsequently, several attempts have been made to improve the availability of VDCs through reliability-aware resource allocation schemes and redundancy provisioning techniques. However, the research to date has not considered the heterogeneity of the underlying physical components. Specifically, it does not consider recent findings showing that failure rates and availability of data center equipments can vary significantly depending on various parameters including their types and ages. To address this limitation, in this paper we propose a High-availability Virtual Infrastructure management framework (Hi-VI) that takes into account the heterogeneity of cloud data center equipments to dynamically provision backup resources in order to ensure required VDC availability. Specifically, we propose a technique to compute the availability of a VDC that considers both (1) the heterogeneity of data center networking and computing equipments in terms of failure rates and availability, and (2) the number of redundant virtual nodes and links provisioned as backups. We then leverage this technique to propose an allocation scheme that jointly provisions resources for VDCs and backups of virtual components with the goal of achieving the required VDC availability while minimizing energy costs. Through simulations, we demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions.

We introduce a new nonlinear control method to globally asymptotically stabilize a class of uncertain nonlinear systems. First, we provide a system reconfiguration method which reconfigures the nonlinear systems with smooth positive functions. Then, we provide a nonlinear controller design method to globally asymptotically stabilize the reconfigured systems by utilizing Lyapunov equations. As a result, a class of uncertain nonlinear systems which have not been treated in the existing results can be globally asymptotically stabilized by our control method. Examples are given for easy following and illustration.

Multi-operand adders that calculate the summation of more than two operands usually consist of compressor trees, which reduce the number of operands to two without any carry propagation, and carry-propagate adders for the two operands in the ASIC implementation. Compressor trees that consist of full adders and half adders cannot be implemented efficiently on LUT-based FPGAs, and carry-chains or dedicated structures have been utilized to produce multi-operand adders on FPGAs. Recent studies indicate that compressor trees can be implemented efficiently on LUTs using Generalized Parallel Counters (GPCs) as the building blocks of compressor trees. This paper addresses the problem of synthesizing compressor trees based on GPCs. Based on the observation that characteristics such as the area, power, and delay correlate roughly to the total number and the maximum level of GPCs, the target problem can be regarded as a minimization problem for the total number of GPCs and the maximum levels of the GPCs, for which an ILP-based approach is proposed. The key point of our formulation is not to model the problem based on the structures of compressor trees like the existing approach, but instead the compression process itself is used to reduce the number of variables and constraints in the ILP formulation. The experimental results demonstrate the advantage of our formulation in terms of the quality and runtime.

Our prior papers proposed a traffic engineering scheme to further localize traffic in peer-assisted content delivery networks (CDNs). This scheme periodically combines the content files and allows them to obtain the combined content files while keeping the price unchanged from the single-content price in order to induce altruistic clients to download content files that are most likely to contribute to localizing network traffic. However, the selection algorithm in our prior work determined which and when content files should be combined according to the cache states of all clients, which is a kind of unrealistic assumption in terms of computational complexity. This paper proposes a new concept of virtual local server to reduce the computational complexity. We could say that the source server in our mechanism has a virtual caching network inside that reflects the cache states of all clients in the ‘actual’ caching network and combines content files based on the virtual caching network. In this paper, without determining virtual caching network according to the cache states of all clients, we approximately estimated the virtual caching network from the cache states of the virtual local server of the local domain, which is the aggregated cache state of only altruistic clients in a local domain. Furthermore, we proposed a content selection algorithm based on a virtual caching network. In this paper, we used news life-cycle model as a content model that had the severe changes in cache states, which was a striking instance of dynamic content models. Computer simulations confirmed that our proposed algorithm successfully localized network traffic.

Pseudo Power Gating (Pseudo PG) is one of gate level power reduction methods for combinational circuits by stopping unnecessary input changes of gates. In Pseudo PG, an extra control signal might be added to a gate and other input changes of the gate are deactivated when the control signal takes the controlling value. To improve the power reduction capability, the paper newly introduces dual-stage Pseudo PG with advanced clustering algorithm where up to two extra control signals are added to a gate if effective. The advanced clustering algorithm selects the first control signal to be compatible with the second control signal based on the propagation of controlling condition via a path, with which candidates of controllable gates excluded by the maximum depth constraint can be controlled. Experimental results show that the proposed dual-stage Pseudo PG method has obtained 23.23% average power reduction with 5.28% delay penalty with respect to the original circuits, and has obtained 10.46% more power reduction with 2.75% delay penalty compared with respect to circuits applying the original single-stage Pseudo PG.

A removable HDD “iVDR” is an international standardized medium, which has HDD features such as a large capacity and high-speed data transfer, and also is removable and compatible. We discuss the concepts of the hardware-specifications designed by the iVDR Consortium and the history of the international standardization activities for iVDR. We also discuss application expansions through these standardization activities.

In this paper, we propose a synthesizable LDPC decoder IP core for the WiMAX system with high parallelism and enhanced error-correcting performance. By taking the advantages of both layered scheduling and fully-parallel architecture, the decoder can fully support multi-mode decoding specified in WiMAX with the parallelism much higher than commonly used partial-parallel layered LDPC decoder architecture. 6-bit quantized messages are split into bit-serial style and 2bit-width serial processing lines work concurrently so that only 3 cycles are required to decode one layer. As a result, 12∼24 cycles are enough to process one iteration for all the code-rates specified in WiMAX. Compared to our previous bit-serial decoder, it doubles the parallelism and solves the message saturation problem of the bit-serial arithmetic, with minor gate count increase. Power synthesis result shows that the proposed decoder achieves 5.83pJ/bit/iteration energy efficiency which is 46.8% improvement compared to state-of-the-art work. Furthermore, an advanced dynamic quantization (ADQ) technique is proposed to enhance the error-correcting performance in layered decoder architecture. With about 2% area overhead, 6-bit ADQ can achieve the error-correcting performance close to 7-bit fixed quantization with improved error floor performance.

We present an algorithm for simultaneously recognizing and localizing planar textured objects in an image. The algorithm can scale efficiently with respect to a large number of objects added into the database. In contrast to the current state-of-the-art on large scale image search, our algorithm can accurately work with query images consisting of several specific objects and/or multiple instances of the same object. Our proposed algorithm consists of two major steps. The first step is to generate a set of hypotheses that provides information about the identities and the locations of objects in the image. To serve this purpose, we extend Bag-Of-Visual-Word (BOVW) image retrieval by incorporating a re-ranking scheme based on the Hough voting technique. Subsequently, in the second step, we propose a geometric verification algorithm based on A Contrario decision framework to draw out the final detection results from the generated hypotheses. We demonstrate the performance of the algorithm on the scenario of recognizing CD covers with a database consisting of more than ten thousand images of different CD covers. Our algorithm yield to the detection results of more than 90% precision and recall within a few seconds of processing time per image.

To facilitate the discovery of mobile apps in personal devices, we present the personalized live homescreen system. The system mines the usage patterns of mobile apps, generates personalized predictions, and then makes apps available at users' hands whenever they want them. Evaluations have verified the promising effectiveness of our system.

Text categorization, especially short text categorization, is a difficult and challenging task since the text data is sparse and multidimensional. In traditional text classification methods, document texts are represented with “Bag of Words (BOW)” text representation schema, which is based on word co-occurrence and has many limitations. In this paper, we mapped document texts to Wikipedia concepts and used the Wikipedia-concept-based document representation method to take the place of traditional BOW model for text classification. In order to overcome the weakness of ignoring the semantic relationships among terms in document representation model and utilize rich semantic knowledge in Wikipedia, we constructed a semantic matrix to enrich Wikipedia-concept-based document representation. Experimental evaluation on five real datasets of long and short text shows that our approach outperforms the traditional BOW method.

In this paper, we propose an adaptive voltage huddle-based distributed-register architecture (AVHDR architecture), which integrates dynamic multiple supply voltages and interconnection delay into high-level synthesis. In AVHDR architecture, voltages can be dynamically assigned for energy reduction. In other words, low supply voltages are assigned to non-critical operations, and leakage power is cut off by turning off the power supply to the sleeping functional units. Next, an AVHDR-based high-level synthesis algorithm is proposed. Our algorithm is based on iterative improvement of scheduling/binding and floorplanning. In the iteration process, the modules in each huddle can be placed close to each other and the corresponding AVHDR architecture can be generated and optimized with floorplanning information. Experimental results show that on average our algorithm achieves 43.9% energy-saving compared with conventional algorithms.

This paper propose a structure of standard cells where the P/N boundary ratio of each cell can be independently customized for near-threshold operation. Lowering the supply voltage is one of the most promising approaches for reducing the power consumption of VLSI circuit, however, this causes an increase of imbalance between rise and fall delays for cells having transistor stacks. Conventional cell library with fixed P/N boundary is not efficient to compensate this delay imbalance. Proposed structure achieves individual P/N boundary ratio optimization for each standard cell, therefore it cancels the imbalance between rise and fall delays at the expense of cell area. Proposed structure is verified using measured result of Ring Oscillator circuits and simulation result of benchmark circuits in 65nm CMOS. The experiments with ISCAS'85 benchmark circuits demonstrate that the standard cell library consisting of the proposed cells reduces the power consumption of the benchmark circuits by 16% on average without increasing the circuit area, compared to that of the same circuit synthesized with a library which is not optimized for the near-threshold operation.

A novel fabrication approach for the amperometric biosensor composed of carbon nanotubes (CNT), a plasma-polymerized film (PPF), hexamineruthenium(III)chloride (RU), and enzyme glucose oxidase (GOD) is reported. The configuration of the electrochemical electrode is multilayer films which contain sputtered gold, lower acetonitrile PPF, CNT, RU, GOD, and upper acetonitrile PPF, sequentially. First, PPF deposited on Au acts as a permselective membrane and as a scaffold for CNT layer formation. Second, PPF directly deposited on GOD acts as a matrix for enzyme immobilization. To facilitate the electrochemical communication between the CNT layer and GOD, CNT was treated with nitrogen plasma. The electron transfer mediator RU play a role as the mediator, in which the electron caused by enzymatic reaction transports to the electrode. The synergy between the electron transfer mediator and CNT provides benefits in terms of lowering the operational potential and enhancing the sensitivity (current). The optimized glucose biosensor revealed a sensitivity of 3.4µA mM-1 cm-2 at +0.4V vs. Ag/AgCl, linear dynamic range of 2.5-19mM, and a response time of 6s.

Lattice-reduction (LR) technique has been adopted to improve the performance and reduce the complexity in MIMO data detection. This paper presents an improved quantization scheme for LR aided MIMO detection based on Gram-Schmidt orthogonalization. For the LR aided detection, the quantization step applies the simple rounding operation, which often leads to the quantization errors. Meanwhile, these errors may result in the detection errors. Hence the purpose of the proposed detection is to further solve the problem of degrading the performance due to the quantization errors in the signal estimation. In this paper, the proposed quantization scheme decreases the quantization errors using a simple tree search with a threshold function. Through the analysis and the simulation results, we observe that the proposed detection can achieve the nearly optimal performance with very low complexity, and require a little additional complexity compared to the conventional LR-MMSE detection in the high Eb/N0 region. Furthermore, this quantization error reduction scheme is also efficient even for the high modulation order.

The recursive transfer method (RTM) is a numerical technique that was developed to analyze scattering phenomena and its formulation is constructed with a difference equation derived from a differential equation by Numerov's discretization method. However, the differential equation to which Numerov's method is applicable is restricted and therefore the application range of RTM is also limited. In this paper, we provide a new discretization scheme to extend RTM formulation using the weak form theory framework. The effectiveness of the proposed formulation is confirmed by microwave scattering induced by a metallic pillar placed asymmetrically in the waveguide. A notable feature of RTM is that it can extract a localized wave from scattering waves even if the tail of the localized wave reaches to the ends of analyzing region. The discrepancy between the experimental and theoretical data is suppressed with in an upper bound determined by the standing wave ratio of the waveguide.