In this paper, we introduce a parallax barrier system that shows high definition autostereoscopy and holds wide viewing zone. The proposed method creates a 4-view parallax barrier system with full display resolution per view by setting aperture ratio to one quarter and using time-division quadplexing, then applies obtained 4-view to 2-view, so that the viewing zone for each eye becomes wider than that from the conventional methods. We build a prototype with two 120,Hz LCD panels and manage to achieve continuous viewing zone with common head-tracking device involved. However, moire patterns and flickers stand out, which are respectively caused by the identical alignments of the color filters on the overlaid LCD panels and a lack of refresh rate of 240,Hz. We successfully remove the moire patterns by changing the structure of the system and inserting a diffuser. We also reduce the flickers by proposing 1-pixel aperture, while stripe shaped noise due to the lack of refresh rate occurs during a blink or a saccade. The stripe noise can be effectively weakened by applying green and magenta anaglyph to the proposed system, where extra crosstalk takes place since the default RGB color filters on LCD panels share certain ranges of wavelength with each other. Although a trade-off turns out to exist between stripe noise and crosstalk from our comparison experiment, results from different settings all hold acceptable quality and show high practicability of our method. Furthermore, we propose a solution that shows possibility to satisfy both claims, where extra color filters with narrow bandwidths are required.

In this paper, we investigate unitary precoder design for multiple-input multiple-output (MIMO) multicasting, where multiple common data streams are sent to a group of users. Assuming that zero-forcing decision feedback equalizers (ZF-DFE) are adopted at the receiver side, we can convert the multicast channel into multiple parallel subchannels. To improve the receiving quality of all data streams, we focus on maximizing the minimal signal-to-noise ratio (SNR) of all data streams. To effectively handle this non-convex optimization problem, we first consider the special case of two data streams and derive the closed-form solution of the SNR vectors for both subchannels. Based on these results, a gradient-based iterative algorithm is developed for the proposed precoder design. For the general case, a Givens rotation-based iterative algorithm is proposed, where at each iteration the original problem of unitary precoder design is transformed into a dual-stream subproblem. Hence it can be solved efficiently by the gradient-based iterative algorithm. Finally, simulation results are presented to demonstrate the outstanding performance of the proposed design.

A fully-integrated double-channel 5-Gb/s/ch 2:1 serializer array is designed and fabricated in a standard 0.18-$mu $m CMOS technology, which can be easily expanded to any even-number-channel array, e.g. 12 channels, by means of arrangement in a parallel manner. Besides two conventional half-rate 2:1 serializers, both phase-locked loop and delay-locked loop techniques are employed locally to deal with the involved clocking-related issues, which make the serializer array self-contained, compact and automatic. The system architecture, circuit and layout designs are discussed and analyzed in detail. The chip occupies a die area of 673,$mu $m$, imes ,$667,$mu $m with a core width of only 450,$mu $m. Measurement results show that it works properly without a need for additional clock channels, reference clocks, off-chip tuning, external components, and so on. From a single supply of 1.8,V, a power of 200,mW is consumed and a single-ended swing of above 300,mV for each channel is achieved.

Wireless communications for the control of industrial equipments need to send a large amount of short packets frequently and to improve frame efficiency. The OFDM frame of wireless local area networks has short preambles that are used for timing synchronization and coarse frequency offset estimation. As the short preambles are repeated in a time domain, they occupies subcarriers intermittently. Therefore, in this paper, a new frame format with OFDM modulation in which data symbols are orthogonally multiplexed with the preamble symbols in the frequency domain is proposed. Two preamble sequences that are based on an IEEE802.11g short preamble sequence and a Zadoff-Chu sequence are examined. The ratio of transmission powers between the pilot subcarrier and the data subcarrier is also varied. The timing synchronization probability with those sequences has been evaluated on different channel models. It is shown through the experiment that the synchronization performance is almost the same as that without data multiplexing at Es/N0 of more than 8dB.

The traffic load of cellular networks varies in both time and spatial domains, causing many base stations (BS) to be under-utilized. Assisted by cell zooming, dynamic BS sleep control is considered as an effective way to improve energy efficiency during low traffic hours. Therefore, how densely the BSs should be deployed with cell zooming and BS sleeping is an important issue. In this paper, we explore the energy-optimal cellular network planning problem with dynamic BS sleeping and cell zooming for the cases in which traffic is uniformly distributed in space but time-varying. To guarantee the quality of multi-class services, an approximation method based on Erlang formula is proposed. Extensive simulations under our predefined scenarios show that about half of energy consumption can be saved through dynamic BS sleeping and power control. Surprisingly, the energy-optimal BS density we obtained is larger than the one without considering BS sleeping. In other words, deploying more BSs may help to save energy if dynamic BS sleeping is executed.

This paper presents a spatial division (SD) transmission method based on two-ray fading that dispenses with the high signal processing cost of multiple-input and multiple-output (MIMO) detection and antennas with narrow beamwidth. We show the optimum array geometries as functions of the transmission distance for providing a concrete array design method. Moreover, we clarify achievable channel capacity considering reflection coefficients that depend on the polarization, incident angle, and dielectric constant. When the ground surface is conductive, for two- and three-element arrays, channel capacity is doubled and tripled, respectively, over that of free space propagation. We also clarify the application limit of this method for a dielectric ground by analyzing the channel capacity's dependency on the dielectric constant. With this method, increased channel capacity by SD transmission can be obtained merely by placing antennas of wireless transceiver sets that have only SISO (single-input and single-output) capability in a two-ray propagation environment. By using formulations presented in this paper for the first time and adding discussions on the adoption of polarization multiplexing, we clarify antenna geometries of SD transmission systems using polarization multiplexing for up to six streams.

Thickness of crystalline layer induced by annealing after rubbing at surface of polyimide film for liquid crystal displays was estimated to be 3--5 nm by grazing-incidence X-ray diffractions with multi incident angles. Agreement of thickness of crystalline layer with that of initially oriented layer suggests polymer orientation induced by rubbing proceeds crystallization by annealing. Furthermore, no in-plane smectic ordering in bottom 20,nm region of polyimide film was suggested.

Reducing accident severity is an effective way to improve road safety. In the literature of accident severity analysis, two main disadvantages exist: most studies use classification accuracy to measure the quality of a classifier which is not appropriate in the condition of unbalanced dataset; the other is the results are not easy to be interpreted by users. Aiming at these drawbacks, a novel multi-objective particle swarm optimization (MOPSO) method is proposed to identify the contributing factors that impact accident severity. By employing Pareto dominance concept, a set of Pareto optimal rules can be obtained by MOPSO automatically, without any pre-defined threshold or variables. Then the rules are used to form a non-ordered classifier. A MOPSO is applied to discover a set of Pareto optimal rules. The accident data of Beijing between 2008 and 2010 are used to build the model. The proposed approach is compared with several rule learning algorithms. The results show the proposed approach can generate a set of accurate and comprehensible rules which can indicate the relationship between risk factors and accident severity.

Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging (MRI) method that can provide direct and quantitative measurements of cerebral blood flow (CBF) of scanned patients. ASL can be utilized as an imaging modality to detect Alzheimer's disease (AD), as brain atrophy of AD patients can be revealed by low CBF values in certain brain regions. However, partial volume effects (PVE), which is mainly caused by signal cross-contamination due to voxel heterogeneity and limited spatial resolution of ASL images, often prevents CBF in ASL from being precisely measured. In this study, a novel PVE correction method is proposed based on pixel-wise voxels in ASL images; it can well handle with the existing problems of blurring and loss of brain details in conventional PVE correction methods. Dozens of comparison experiments and statistical analysis also suggest that the proposed method is superior to other PVE correction methods in AD diagnosis based on real patients data.

This letter proposes an efficient lossless compression method for high dynamic range (HDR) images in OpenEXR format. The proposed method transforms an HDR image to an indexed image and packs the histogram of the indexed image. Finally the packed image is losslessly compressed by using any existing lossless compression algorithm such as JPEG 2000. Experimental results show that the proposed method reduces the bit rate of compressed OpenEXR images compared with equipped lossless compression methods of OpenEXR format.

Network virtualization is an essential technology for cloud datacenters that provide multi-tenancy services. SDN-enabled datacenters have introduced an edge-overlay (distributed tunneling) model to construct virtual tenant networks. The edge-overlay model generally uses L2-in-L3 tunneling protocols like VXLAN. However, the tunneling-based edge-overlay model has some performance and compatibility problems. We have proposed a yet another overlay approach without using IP tunneling. Our model leverages two methods, OpenFlow-based Virtual/Physical MAC address translation and host-based VLAN ID usage. The former method replaces VMs' MAC addresses to physical servers' ones, which prevents frame encapsulation as well as unnecessary MAC address learning by physical switches. The later method breaks a limitation of the number of VLAN-based virtual tenant networks (4094) by allocating entire VLAN ID space to each physical server and by mapping VLAN ID to VM with OpenFlow controller support. In our model, any special hardware equipment like OpenFlow hardware switches is not required and only software-based virtual switches and the controller are used. In this paper, we evaluated the performance of the proposed model comparing with the tunneling model using 40GbE environment. The results show that the performance of VM-to-VM communication with the proposed model is close to that of physical communication and exceeds 10Gbps throughput with large TCP segment, and the proposed model shows better scalability for the number of VMs.

The MR image segmentation is always a challenging problem because of the intensity inhomogeneity. Many existing methods don't reach their expected segmentations; besides their implementations are usually complicated. Therefore, we originally interleave the extended Otsu segmentation with bias field estimation in an energy minimization. Via our proposed method, the optimal segmentation and bias field estimation are achieved simultaneously throughout the reciprocal iteration. The results of our method not only satisfy the required classification via its applications in the synthetic and the real images, but also demonstrate that our method is superior to the baseline methods in accordance with the performance analysis of JS metrics.

This paper proposes a novel method for determining a three-dimensional (3D) bounding box to estimate pose (position and orientation) and size of a 3D object corresponding to a segmented object region in an image acquired by a single calibrated camera. The method is designed to work upon an object on the ground and to determine a bounding box aligned to the direction of the object, thereby reducing the number of degrees of freedom in localizing the bounding box to 5 from 9. Observations associated with the structural properties of back-projected object regions on the ground are suggested, which are useful for determining the object points expected to be on the ground. A suitable base is then estimated from the expected on-ground object points by applying to them an assumption of bilateral symmetry. A bounding box with this base is finally constructed by determining its height, such that back-projection of the constructed box onto the ground minimally encloses back-projection of the given object region. Through experiments with some 3D-modelled objects and real objects, we found that a bounding box aligned to the dominant direction estimated from edges with common direction looks natural, and the accuracy of the pose and size is enough for localizing actual on-ground objects in an industrial working space. The proposed method is expected to be used effectively in the fields of smart surveillance and autonomous navigation.

In this paper, an adaptive expansion strategy (AES) is proposed for multiple-input/multiple-output (MIMO) detection in the presence of circular signals. By exploiting channel properties, the AES classifies MIMO channels into three types: excellent, average and deep fading. To avoid unnecessary branch-searching, the AES adopts single expansion (SE), partial expansion (PE) and full expansion (FE) for excellent channels, average channels and deep fading channels, respectively. In the PE, the non-circularity of signal is exploited, and the widely linear processing is extended from non-circular signals to circular signals by I (or Q) component cancellation. An analytical performance analysis is given to quantify the performance improvement. Simulation results show that the proposed algorithm can achieve quasi-optimal performance with much less complexity (hundreds of flops/symbol are saved) compared with the fixed-complexity sphere decoder (FSD) and the sphere decoder (SD).

In this paper, we present an efficient time-of-arrival (TOA)-based localization method for wireless sensor networks. The goal of a localization system is to accurately estimate the geographic location of a wireless device. In real wireless sensor networks, accurately estimating mobile device location is difficult because of the presence of various errors. Therefore, localization methods have been studied in recent years. In indoor environments, the accuracy of wireless localization systems is affected by non-line-of-sight (NLOS) errors. The presence of NLOS errors degrades the performance of wireless localization systems. In order to effectively estimate the location of the mobile device, NLOS errors should be recognized and mitigated in indoor environments. In the TOA-based ranging method, the distance between the two wireless devices can be computed by multiplying a signal's propagation delay time by the speed of light. TOA-based localization measures the distance between the mobile station (MS) and three or more base stations (BSs). However, each of the NLOS errors of the measured distance between the i-th BS and the MS is different due to dissimilar obstacles in the direct signal path between the two nodes. In order to accurately estimate the location in a TOA-based localization system, an optimized localization algorithm that selects three measured distances with fewer NLOS errors is necessary. We present an efficient TOA-based localization scheme that combines three selected BSs in wireless sensor networks. This localization scheme yields improved localization performance in wireless sensor networks. In this paper, performance tests are performed, and the simulation results are verified through comparisons between various localization methods and the proposed method. As a result, proposed localization scheme using BS selection achieves remarkably better localization performance than the conventional methods. This is verified by experiments in real environments, and demonstrates a performance analysis in NLOS environments. By using BS selection, we will show an efficient and effective TOA-based localization scheme in wireless sensor networks.

A discriminative reference-based method for scene image categorization is presented in this letter. Reference-based image classification approach combined with K-SVD is approved to be a simple, efficient, and effective method for scene image categorization. It learns a subspace as a means of randomly selecting a reference-set and uses it to represent images. A good reference-set should be both representative and discriminative. More specifically, the reference-set subspace should well span the data space while maintaining low redundancy. To automatically select reference images, we adapt affinity propagation algorithm based on data similarity to gather a reference-set that is both representative and discriminative. We apply the discriminative reference-based method to the task of scene categorization on some benchmark datasets. Extensive experiment results demonstrate that the proposed scene categorization method with selected reference set achieves better performance and higher efficiency compared to the state-of-the-art methods.

An efficient subcarrier allocation scheme of a supporting cell is proposed to recover the communication of faulty cell users in an OFDM-based wireless system. With the proposed subcarrier allocation scheme, the number of subcarriers allocated to faulty cell users is maximized while the average throughput of supporting cell users is maintained at a desired level. To find the maximum number of subcarriers allocated to faulty cell users, the average throughput of the subcarrier with the k-th smallest channel gain in a subcarrier group is derived by an inductive method. It is shown by simulation that the proposed subcarrier allocation scheme can provide more subcarriers to faulty cell users than the random selection subcarrier allocation scheme.

Sound source localization (SSL), with a binaural input in practical environments, is a challenging task due to the effects of noise and reverberation. In psychoacoustic research field, one of the theories to explain the mechanism of human perception in such environments is the well-known equalization-cancellation (EC) model. Motivated by the EC theory, this paper investigates a binaural SSL method by integrating EC procedures into a beamforming technique. The principle idea is that the EC procedures are first utilized to eliminate the sound signal component at each candidate direction respectively; direction of sound source is then determined as the direction at which the residual energy is minimal. The EC procedures applied in the proposed method differ from those in traditional EC models, in which the interference signals in rooms are accounted in E and C operations based on limited prior known information. Experimental results demonstrate that our proposed method outperforms the traditional SSL algorithms in the presence of noise and reverberation simultaneously.

This note presents a new approach for the robustness of Hurwitz polynomials under coefficient perturbation. The s-domain Hurwitz polynomial is transformed to the z-domain polynomial by the bilinear transformation. Then an approach based on the Rouché theorem introduced in the literature is applied to compute a crude bound for the allowable coefficient variation such that the perturbed polynomial maintains the Hurwitz stability property. Three methods to obtain improved bounds are also suggested. The results of this note are computationally more efficient than the existing direct s-domain approaches especially for polynomials of higher degree. Furthermore examples indicate that the exact bound for the coefficient variation can be obtained in some cases.

Multi-user MIMO (MU-MIMO) improves the system channel capacity by employing the transmission between a base station and multiple user terminals (UTs). Block Diagonalization (BD) has been proposed in order to realize MU-MIMO broadcast transmission. The BD algorithm cancels inter-user interference by creating the weights so that the channel matrixes for the other users are set to be zero matrixes. However, when the number of transmit antennas is equals to the total number of received antennas, the transmission rate by the BD algorithm is decreased. This paper proposes a new antenna selection method at the UTs to reduce the number of nulls for the other users except an intended user by the BD algorithm. It is verified via bit error rate (BER) evaluation that the proposed method is effective compared to the conventional BD algorithm, especially, when the number of users is increased with a low bit rate. Moreover, this paper evaluates the transmission rate based on IEEE802.11ac standard when considering BD algorithm with ideal user scheduling. Although the number of equivalent receive antenna is only one by the proposed method when the number of antennas at the the UT is two, it is shown that the transmission rate by the proposed method is higher than that by the conventional BD algorithm when the SNR is low even in the condition on user scheduling.