In a sector of a single cell, due to the fading characteristic of wireless channels, several decode-and-forward relay stations are deployed to form a two-hop relay-assisted multicast system. We propose two schemes for the system, the first scheme combines the use of space-time code and distributed space-time code (DSTC), and the second one combines the use of DSTC and maximum ratio combining. We give an outage probability analysis for both of them. Based on this analysis, we manage to maximize the spectral efficiency under a preset outage probability confinement by finding out the optimal power allocation and relay location strategies. We use genetic algorithms to verify our analysis and numerical results show that the schemes proposed by us significantly outperform the scheme in previous work. We also show the effect of path loss exponent on the optimal strategy.

High voltage DC contactors, for operation at voltage levels up to at least about 300,volts, find their increasing markets in applications such as electrical vehicles and aircrafts in which size and weight of cables are of extreme importance. The copper bridge-type contact, cooperated with magnetic field provided by permanent magnets and sealed in an arc chamber filled with high pressure gases, is a mainly used structure to interrupt the DC arc rapidly. Arc characteristic in different gases at different pressure varies greatly. This paper is focused on the arc characteristics of the bridge-type contact system when magnetic field is applied with nitrogen and gas at different pressure. The pressure of the gases varies from 1,atm to 2.5,atm. Arc characteristics, such as arc durations at different stages and arc motions in those gases are comparatively studied. The results are instructive for choosing the suitable arcing atmosphere in a DC bridge-type arc chamber of a contactor.

Most of the previous work on power optimization regarded the capacity of battery power as an ideal constant value. In fact, experiments showed that 30% of the total battery capacity was wasted by improper discharge pattern [1]. In this letter, a battery-aware task scheduling protocol which harnesses one of the typical characteristics of batteries, i.e., battery recovery, is proposed to extend usage time for smart phones. The key idea is to adjust the working schedule of the components in smart phones for more energy recovering. Experiments show that when the proposed protocol is applied in an online music application, as much as 9% lifespan extension for batteries can be obtained.

Sensing and reproduction of precise sound-space information is important to realize highly realistic audio communications. This study was conducted to realize high-precision sensors of 3D sound-space information for transmission to distant places and for preservation of sound data for the future. Proposed method comprises a compact and spherical object with numerous microphones. Each recorded signal from multiple microphones that are uniformly distributed on the sphere is simply weighted and summed to synthesize signals to be presented to a listener's left and right ears. The calculated signals are presented binaurally via ordinary binaural systems such as headphones. Moreover, the weight can be changed according to a human's 3D head movement. A human's 3D head movement is well known to be a crucially important factor to facilitate human spatial hearing. For accurate spatial hearing, 3D sound-space information is acquired as accurately reflecting the listener's head movement. We named the proposed method SENZI (Symmetrical object with ENchased ZIllion microphones). The results of computer simulations demonstrate that our proposed SENZI outperforms a conventional method (binaural Ambisonics). It can sense 3D sound-space with high precision over a wide frequency range.

This paper proposes a sound source orientation estimation method that is suitable for a distributed microphone arrangement. The proposed method is based on orientation-extended beamforming (OEBF), which has four features: (a) robustness against reverberations, (b) robustness against noises, (c) free arrangements of microphones and (d) feasibility for real-time processing. In terms of (a) and (c), since OEBF is based on a general propagation model using transfer functions (TFs) that include all propagation phenomena such as reflections and diffractions, OEBF causes no model errors for the propagation phenomena, and is applicable to arbitrary microphone arrangements. Regarding (b), OEBF overcomes noise effects by incorporating three additional processes (Amplitude extraction, time-frequency mask and histogram integration) that are also proposed in this paper. As for (d), OEBF is executable in real-time basis as the execution process is the same as usual beamforming processes. A numerical experiment was performed to confirm the theoretical validity of OEBF. The results showed that OEBF was able to estimate sound source positions and orientations very precisely. Practical experiments were carried out using a 96-channel microphone array in real environments. The results indicated that OEBF worked properly even under reverberant and noisy environments and the averaged estimation error was given only 4°.

Decimation and interpolation methods are utilized in image coding for low bit rate image coding. However, the decimation filter (prefilter) and the interpolation filter (postfilter) are irreversible with each other since the prefilter is a wide matrix (a matrix whose number of columns are larger than that of rows) and the postfilter is a tall one (a matrix whose number of rows are larger than that of columns). There will be some distortions in the reconstructed image even without any compression. The method of interpolation-dependent image downsampling (IDID) was used to tackle the problem of producing optimized downsampling images, which led to the optimized prefilter of a given postfilter. We propose integrating the IDID with time-domain lapped transforms (TDLTs) to improve image coding performance.

This paper describes a soft-error tolerant and margin-enhanced nMOS-pMOS reversed 6T SRAM cell. The 6T SRAM bitcell comprises pMOS access and driver transistors, and nMOS load transistors. Therefore, the nMOS and pMOS masks are reversed in comparison with those of a conventional bitcell. In scaled process technology, The pMOS transistors present advantages of small random dopant fluctuation, strain-enhanced saturation current, and small soft-error sensitivity. The four-pMOS and two-nMOS structure improves the soft-error rate plus operating margin. We conduct SPICE and neutron-induced soft-error simulations to evaluate the n-p reversed 6T SRAM bitcell in 130-nm to 22-nm processes. At the 22-nm node, a multiple-cell-upset and single-bit-upset SERs are improved by 34% and 51% over a conventional 6T cell. Additionally, the static noise margin and read cell current are 2.04× and 2.81× improved by leveraging the pMOS benefits.

This paper studies an adaptive high gain observer design for nonlinear systems which have lower triangular nonlinearity with Lipschitz coefficient, depending on the control input. Because the gain of the proposed observer is tuned automatically by a simple update law, our design approach doesn't need any information about the Lipschitz constant. Also, it is shown that under some assumptions, the dynamic gain of the proposed observer is bounded and its estimation error converges to zero asymptotically. Finally, a numerical example is given to verify the effectiveness of our design approach.

We design a full-order observer for discrete-time linear time-invariant systems with constant output delays. The observer design is based on the output delay model expressed by a two-dimensional state variable, with discrete-time and space independent variables. Employing a discrete-time state transformation, we construct an explicit strict Lyapunov function that enables us to prove the global exponential stability of the full-order observer error system with an explicit estimate of the exponential decay rate. The numerical example demonstrates the design of the full-order observer and illustrates the validity of the exponential stability.

The IEEE 802.11 distributed coordinated function (DCF) adopts carrier sense multiple access with collision avoidance (CSMA/CA) as its medium access control (MAC) protocol. In a wireless local area network (WLAN) stations (STAs) congested situation, the performance of the WLAN system is significantly degraded due to a collision between the STAs. In this paper, we propose a simple method that decreases the number of frame collisions. After a successful transmission, the proposed method refrains from transmission during certain time which is defined as post-inter-frame space (Post-IFS). This mechanism improves the system performance including the throughput characteristics and access delay by reducing the number of competing STAs. The length of the Post-IFS is a key factor in improving the system performance for the proposed method. If the access point (AP) can estimate the optimal value of the Post-IFS, collision-free operation similar to that in centralized control is performed. Even if the optimal Post-IFS is not estimated, the number of competing STAs and the collision probability are decreased. Computer simulations verify that the proposed method achieves 40% higher system throughput compared to the conventional CSMA/CA for a network with 50 STAs.

Researchers have developed several social-based routing protocols for delay tolerant networks (DTNs) over the past few years. Two main routing metrics to support social-based routing in DTNs are centrality and similarity metrics. These two metrics help packets decide how to travel through the network to achieve short delay or low drop rate. This study presents a new routing scheme called Community-Relevance based Opportunistic routing (CROP). CROP uses a different message forwarding approach in DTNs by combining community structure with a new centrality metric called community relevance. One fundamental change in this approach is that community relevance values do not represent the importance of communities themselves. Instead, they are computed for each community-community relationship individually, which means that the level of importance of one community depends on the packet's destination community. The study also compares CROP with other routing algorithms such as BubbleRap and SimBet. Simulation results show that CROP achieves an average delivery ratio improvement of at least 30% and can distribute packets more fairly within the network.

In this paper, we propose a novel method for road sign detection and recognition in complex scene real world images. Our algorithm consists of four basic steps. First, we employ a regional contrast based bottom-up visual saliency method to highlight the traffic sign regions, which usually have dominant color contrast against the background. Second, each type of traffic sign has special color distribution, which can be explored by top-down visual saliency to enhance the detection precision and to classify traffic signs into different categories. A bag-of-words (BoW) model and a color name descriptor are employed to compute the special-class distribution. Third, the candidate road sign blobs are extracted from the final saliency map, which are generated by combining the bottom-up and the top-down saliency maps. Last, the color and shape cues are fused in the BoW model to express blobs, and a support vector machine is employed to recognize road signs. Experiments on real world images show a high success rate and a low false hit rate and demonstrate that the proposed framework is applicable to prohibition, warning and obligation signs. Additionally, our method can be applied to achromatic signs without extra processing.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) combined with time division multiplexing (OFDM/TDM) based on frequency domain equalization (FDE) has been proposed to reduce the high peak-to-average power ratio (PAPR) of OFDM and improve the bit error rate (BER) performance in comparison to the conventional OFDM. However, due to the nonlinearity of the high-power amplifier (HPA) at the transmitter and the fact that the PAPR problem is not completely eliminated, the nonlinear noise due to HPA saturation still degrades the BER performance. In this paper, we theoretically evaluate the effect of nonlinear HPA on the performance of MIMO-OFDM/TDM using a minimum-mean square-error frequency-domain equalizer (MMSE-FDE). We determine the equalization weights while taking into account the negative effect of HPA saturation and then evaluate the system performance in terms of average BER and ergodic capacity by way of both, numerical and computer simulation. Our simulation results have shown that appropriate system design can make MIMO-OFDM/TDM more robust against nonlinear degradation due to HPA saturation in comparison to MIMO-OFDM while reducing required signal-to-noise ratio (SNR) for the given target BER.

In the optimization of decision diagrams, variable reordering approaches are often used to minimize the number of nodes. However, such approaches are less effective for analysis of multi-state systems given by monotone structure functions. Thus, in this paper, we propose algorithms to minimize the number of edges in an edge-valued multi-valued decision diagram (EVMDD) for fast analysis of multi-state systems. The proposed algorithms minimize the number of edges by grouping multi-valued variables into larger-valued variables. By grouping multi-valued variables, we can reduce the number of nodes as well. To show the effectiveness of the proposed algorithms, we compare the proposed algorithms with conventional optimization algorithms based on a variable reordering approach. Experimental results show that the proposed algorithms reduce the number of edges by up to 15% and the number of nodes by up to 47%, compared to the conventional ones. This results in a speed-up of the analysis of multi-state systems by about three times.

This paper presents an efficient multi-service allocation scheme for the digital television terrestrial broadcasting systems in which the fixed service is modulated by orthogonal frequency division multiplexing and quadrature amplitude modulation (OFDM/QAM) with larger FFT size and the added mobile service is modulated by OFDM and offset quadrature amplitude modulation (OQAM) with smaller FFT size. The two different types of services share one 8MHz broadcasting channel. The isotropic orthogonal transform algorithm (IOTA) is chosen as the shaping filter for OQAM because of its isotropic convergence in time and frequency domain and the proper FFT size is selected to maximum the transmission capacity under mobile environment. The corresponding transceiver architecture is also proposed and analyzed. Simulations show that the newly added mobile service generates much less out-of-band interference to the fixed service and has a better performance under fast fading wireless channels.

The data rate of VLSI interconnections has been increasing according to the demand for high-speed operation of semiconductors such as CPUs. To realize high performance VLSI systems, high-speed data communication has become an important factor. However, at high-speed data rates, it is difficult to achieve accurate communication without bit errors because of inter-symbol interference (ISI). This paper presents high-speed data communication techniques for VLSI systems using Tomlinson-Harashima Precoding (THP). Since THP can eliminate the ISI with limiting average and peak power of transmitter signaling, THP is suitable for implementing advanced low-voltage VLSI systems. In this paper, 4-PAM (Pulse amplitude modulation) with THP has been employed to achieve high-speed data communication in VLSI systems. Simulation results show that THP can remove the ISI without increasing peak and average power of a transmitter. Moreover, simulation results clarify that multiple-valued data communication is very effective to reduce implementation costs for realizing high-speed serial links.

Reversible logic is becoming more and more popular due to the fact that many novel technologies such as quantum computing, low power CMOS circuit design or quantum optical computing are becoming more and more realistic. In quantum computing, reversible computing is the main venue for the realization and design of classical functions and circuits. We present a new approach to synthesis of reversible circuits using Kronecker Functional Lattice Diagrams (KFLD). Unlike many of contemporary algorithms for synthesis of reversible functions that use n×n Toffoli gates, our method synthesizes functions using 3×3 Toffoli gates, Feynman gates and NOT gates. This reduces the quantum cost of the designed circuit but adds additional ancilla bits. The resulting circuits are always regular in a 4-neighbor model and all connections are predictable. Consequently resulting circuits can be directly mapped in to a quantum device such as quantum FPGA [14]. This is a significant advantage of our method, as it allows us to design optimum circuits for a given quantum technology.

NAND flash storage devices, such as eMMCs and microSD cards, are now widely used in mobile devices. In this paper, we propose a novel buffer replacement scheme for mobile NAND flash storages. It efficiently improves write performance by evicting pages flash-friendly and maintains high cache hit ratios by managing pages in order of recency. Our experimental results show that the proposed scheme outperforms the best performing scheme in the recent literature, Sp.Clock, by 48%.

A top-k keyword query in relational databases returns k trees of tuples — where the tuples containing the query keywords are connected via primary key-foreign key relationships — in the order of relevance to the query. Existing works are classified into two categories: 1) the schema-based approach and 2) the schema-free approach. We focus on the former utilizing database schema information for more effective ranking of the query results. Ranking measures used in existing works can be classified into two categories: 1) the size of the tree (i.e., the syntactic score) and 2) ranking measures, such as TF-IDF, borrowed from the information retrieval field. However, these measures do not take into account semantic relevancy among relations containing the tuples in the query results. In this paper, we propose a new ranking method that ranks the query results by utilizing semantic relevancy among relations containing the tuples at the schema level. First, we propose a structure of semantically strongly related relations, which we call the strongly related tree (SRT). An SRT is a tree that maximally connects relations based on the lossless join property. Next, we propose a new ranking method, SRT-Rank, that ranks the query results by a new scoring function augmenting existing ones with the concept of the SRT. SRT-Rank is the first research effort that applies semantic relevancy among relations to ranking the results of keyword queries. To show the effectiveness of SRT-Rank, we perform experiments on synthetic and real datasets by augmenting the representative existing methods with SRT-Rank. Experimental results show that, compared with existing methods, SRT-Rank improves performance in terms of four quality measures — the mean normalized discounted cumulative gain (nDCG), the number of queries whose top-1 result is relevant to the query, the mean reciprocal rank, and the mean average precision — by up to 46.9%, 160.0%, 61.7%, and 63.8%, respectively. In addition, we show that the query performance of SRT-Rank is comparable to or better than those of existing methods.

Independent and identically distributed (i.i.d) assumptions are commonly used in the machine learning community. However, social media data violate this assumption due to the linkages. Meanwhile, with the variety of data, there exist many samples, i.e., Universum, that do not belong to either class of interest. These characteristics pose great challenges to dealing with social media data. In this letter, we fully take advantage of Universum samples to enable the model to be more discriminative. In addition, the linkages are also taken into consideration in the means of social dimensions. To this end, we propose the algorithm Semi-Supervised Linked samples Feature Selection with Universum (U-SSLFS) to integrate the linking information and Universum simultaneously to select robust features. The empirical study shows that U-SSLFS outperforms state-of-the-art algorithms on the Flickr and BlogCatalog.