Determining the rotation angle between two images is essential when comparing images that may include rotational variation. While there are three representative methods that utilize the phases of Zernike moments (ZMs) to estimate rotation angles, very little work has been done to compare the performances of these methods. In this paper, we compare the performances of these three methods and propose a new, angular radial transform (ART)-based method. Our method extends Revaud et al.'s method [1] and uses the phase of angular radial transform coefficients instead of ZMs. We show that our proposed method outperforms the ZM-based method using the MPEG-7 shape dataset when computation times are compared or in terms of the root mean square error vs. coverage.

The impact of co-channel deployment of femtocells on existing macro-cellular systems is investigated considering the use of techniques to resolve the loud neighbor problem. There are several approaches to this aim, for example, femtocell power control, interference coordination, and opening access to femtocells. Of these, coordinated scheduling, including power control, and their impact will be the main focus of this work. In the context of 3GPP-LTE, we examine under various operational scenarios the performance in terms of the average and 5% worst user throughput, a useful measure of fairness among users, both for femto and macro cells. Although recent studies have shown that co-channel femtocell has a minor impact on the macrocell performance in average sense, a non-negligible percentage of users may lose their opportunity to get satisfactory data service and, hence, we focus more on the 5% worst users.

This paper proposes a video-quality estimation method based on a reduced-reference model for realtime quality monitoring in video streaming services. The proposed method chooses representative-luminance values for individual original-video frames at a server side and transmits those values, along with the pixel-position information of the representative-luminance values in each frame. On the basis of this information, peak signal-to-noise ratio (PSNR) values at client sides can be estimated. This enables realtime monitoring of video-quality degradation by transmission errors. Experimental results show that accurate PSNR estimation can be achieved with additional information at a low bit rate. For SDTV video sequences which are encoded at 1 to 5 Mbps, accurate PSNR estimation (correlation coefficient of 0.92 to 0.95) is achieved with small amount of additional information of 10 to 50 kbps. This enables accurate realtime quality monitoring in video streaming services without average video-quality degradation.

In this paper, we propose an optimized virtual re-convergence system especially to reduce the visual fatigue caused by binocular stereoscopy. Our unique idea to reduce visual fatigue is to utilize the virtual re-convergence based on the optimized disparity-map that contains more depth information in the negative disparity area than in the positive area. Therefore, our system facilitates a unique search-range scheme, especially for negative disparity exploration. In addition, we used a dedicated method, using a so-called Global-Shift Value (GSV), which are the total shift values of each image in stereoscopy to converge a main object that can mostly affect visual fatigue. The experimental result, which is a subjective assessment by participants, shows that the proposed method makes stereoscopy significantly comfortable and attractive to view than existing methods.

In this paper, we propose integration of multimodal features using conditional random fields (CRFs) for the segmentation of broadcast news stories. We study story boundary cues from lexical, audio and video modalities, where lexical features consist of lexical similarity, chain strength and overall cohesiveness; acoustic features involve pause duration, pitch, speaker change and audio event type; and visual features contain shot boundaries, anchor faces and news title captions. These features are extracted in a sequence of boundary candidate positions in the broadcast news. A linear-chain CRF is used to detect each candidate as boundary/non-boundary tags based on the multimodal features. Important interlabel relations and contextual feature information are effectively captured by the sequential learning framework of CRFs. Story segmentation experiments show that the CRF approach outperforms other popular classifiers, including decision trees (DTs), Bayesian networks (BNs), naive Bayesian classifiers (NBs), multilayer perception (MLP), support vector machines (SVMs) and maximum entropy (ME) classifiers.

With the purpose of improving the performance of next generation wireless networks, cooperative relaying (CoR) and network coding (NC) are promising techniques. The number of time slots required for NC in bidirectional transmission is less than that required for CoR, and hence, NC can achieve higher throughput performance than CoR. However, the disadvantage of NC is that asymmetric traffic ratio conditions might cause a significant decrease in the bidirectional throughput. In contrast, CoR is robust to asymmetric traffic ratio conditions. In this paper, in order to improve the throughput of NC even under asymmetric traffic ratio conditions, we propose an opportunistic scheduling scheme for hybrid NC and CoR. In the proposed scheduling scheme, the transmission protocol with best throughput performance can be adaptively selected based on instantaneous channel state information. Computer simulation results reveal that the proposed scheduling scheme not only achieve higher throughput than the conventional scheduling scheme but is also robust against asymmetric traffic ratio conditions. By adjusting the scheduler's parameter, the proposed scheduling scheme can provide a tradeoff between the throughput and the traffic ratio. Moreover, in certain cases, maximizing the throughput of NC and guaranteeing the offered traffic ratio can be achieved at the same time.

In this paper, we propose a new low power nonvolatile counter unit based on Magnetic Tunnel Junction (MTJ) with fine-grained power gating. The proposed counter unit consists of only a single latch with two MTJs. We verify the basic operation and estimate the power consumption of the proposed counter unit. The operating power consumption of the proposed nonvolatile counter unit is smaller than the conventional one below 140 kHz. The power of the proposed unit is 74.6% smaller than the conventional one at low frequency.

In this paper, a 60 nm-thick ferroelectric film of poly(vinylidene fluoride–trifluoroethylene) on a flexible substrate of aluminum foil was fabricated and characterized. Compared to pristine silicon wafer, Al-foil has very large root-mean-square (RMS) roughness, thus presenting challenges for the fabrication of flat and uniform electronic devices on such a rough substrate. In particular, RMS roughness affects the leakage current of dielectrics, the uniformity of devices, and the switching time in ferroelectrics. To avoid these kinds of problems, a new thin film fabrication method adopting a detach-and-transfer technique has been developed. Here, 'detach' means that the ferroelectric film is detached from a flat substrate (sacrificial substrate), and 'transfer' refers to the process of the detached film being moved onto the rough substrate (main substrate). To characterize the dielectric property of the transferred film, polarization and voltage relationships were measured, and the results showed that a hysteresis loop could be obtained with low leakage current.

In this paper, a logarithmic adaptive quantization projection (LAQP) algorithm for digital watermarking is proposed. Conventional quantization index modulation uses a fixed quantization step in the watermarking embedding procedure, which leads to poor fidelity. Moreover, the conventional methods are sensitive to value-metric scaling attack. The LAQP method combines the quantization projection scheme with a perceptual model. In comparison to some conventional quantization methods with a perceptual model, the LAQP only needs to calculate the perceptual model in the embedding procedure, avoiding the decoding errors introduced by the difference of the perceptual model used in the embedding and decoding procedure. Experimental results show that the proposed watermarking scheme keeps a better fidelity and is robust against the common signal processing attack. More importantly, the proposed scheme is invariant to value-metric scaling attack.

In this paper, a novel framework for extracting visual feature-based keyword relationships from an image database is proposed. From the characteristic that a set of relevant keywords tends to have common visual features, the keyword relationships in a target image database are extracted by using the following two steps. First, the relationship between each keyword and its corresponding visual features is modeled by using a classifier. This step enables detection of visual features related to each keyword. In the second step, the keyword relationships are extracted from the obtained results. Specifically, in order to measure the relevance between two keywords, the proposed method removes visual features related to one keyword from training images and monitors the performance of the classifier obtained for the other keyword. This measurement is the biggest difference from other conventional methods that focus on only keyword co-occurrences or visual similarities. Results of experiments conducted using an image database showed the effectiveness of the proposed method.

The development of new technologies has undoubtedly promoted the advances of modern education, among which Virtual Reality (VR) technologies have made the education more visually accessible for students. However, classroom education has been the focus of VR applications whereas not much research has been done in promoting sports education using VR technologies. In this paper, an immersive VR system is designed and implemented to create a more intuitive and visual way of teaching tennis. A scalable system architecture is proposed in addition to the hardware setup layout, which can be used for various immersive interactive applications such as architecture walkthroughs, military training simulations, other sports game simulations, interactive theaters, and telepresent exhibitions. Realistic interaction experience is achieved through accurate and robust hybrid tracking technology, while the virtual human opponent is animated in real time using shader-based skin deformation. Potential future extensions are also discussed to improve the teaching/learning experience.

We propose a new three-dimensional (3D) NAND flash memory array having Tied Bit-line and Ground Select Transistor (TiGer) [1]. Channels are stacked in the vertical direction to increase the memory density without the device size scaling. To distinguish stacked channels, a novel operation scheme is introduced instead of adding supplementary control gates. The stacked layers are selected by using ground select line (GSL) and common source line (CSL). Device structure and fabrication process are described. Operation scheme and simulation results for program inhibition are also discussed.

In this paper, a Schmitt Trigger based 10T SRAM (ST 10T SRAM) cell with the vertical MOSFET is proposed for low supply voltage operation, and its impacts on cell size, stability and speed performance are investigated. The proposed ST 10T SRAM cell with the vertical MOSFET achieves smaller cell size than the ST 10T SRAM cell with the conventional planar MOSFET. Moreover, the proposed SRAM cell realizes large and constant static noise margin (SNM) against bottom node resistance of the vertical MOSFET without any architectural changes from the present 6T SRAM architecture. The proposed SRAM cell also suppresses the degradation of the read time of the ST 10T SRAM cell due to the back-bias effect free characteristic of the vertical MOSFET. The proposed ST 10T SRAM cell with the vertical MOSFET is a superior SRAM cell for low supply voltage operation with a small cell size, stable operation, and fast speed performance with the present 6T SRAM architecture.

We have investigated the low-power circuit applicability of hetero-gate-dielectric tunneling field-effect transistors (HG TFETs). Based on the device-level comparison of HG, SiO2-only and high-k-only TFETs, their circuit performance and energy consumption have been discussed. It has been shown that HG TFETs can deliver 14400x higher performance than the SiO2-only TFETs and 17x higher performance than the high-k-only TFETs due to its higher on current and lower capacitance at the same static power, same power supply. It has been revealed that HG TFETs have better voltage scalability than the others. It is because HG TFETs dissipate only 8% of energy consumption of SiO2-only TFETs and 17% of that of high-k-only TFETs under the same performance condition.

An important and widely considered signal identification technique for cognitive radios is cyclostationarity-based feature detection because this method does not require time and frequency synchronization and prior information except for information concerning cyclic autocorrelation features of target signals. This paper presents the development and experimental evaluation of cyclostationarity-based signal identification equipment. A spatial channel emulator is used in conjunction with the equipment that provides an environment to evaluate realistic spectrum sharing scenarios. The results reveal the effectiveness of the cyclostationarity-based signal identification methodology in realistic spectrum sharing scenarios, especially in terms of the capability to identify weak signals.

Setting relays can address the shadowing problem between a transmitter (Tx) and a receiver (Rx). Moreover, the Multiple-Input Multiple-Output (MIMO) technique has been introduced to improve wireless link capacity. The MIMO technique can be applied in relay network to enhance system performance. However, the efficiency of relaying schemes and relay placement have not been well investigated with experiment-based study. This paper provides a propagation measurement campaign of a MIMO two-hop relay network in 5 GHz band in an L-shaped corridor environment with various relay locations. Furthermore, this paper proposes a Relay Placement Estimation (RPE) scheme to identify the optimum relay location, i.e. the point at which the network performance is highest. Analysis results of channel capacity show that relaying technique is beneficial over direct transmission in strong shadowing environment while it is ineffective in non-shadowing environment. In addition, the optimum relay location estimated with the RPE scheme also agrees with the location where the network achieves the highest performance as identified by network capacity. Finally, the capacity analysis shows that two-way MIMO relay employing network coding has the best performance while cooperative relaying scheme is not effective due to shadowing effect weakening the signal strength of the direct link.

As MOS transistors are scaled down, the impact of randomly placed discrete charge (impurity atoms, traps and surface states) on device characteristics rapidly increases. Significant variability caused by random dopant fluctuation (RDF) is a direct result of this, which urges the adoption of new device architectures (ultra-thin body SOI FETs and FinFETs) which do not use impurity for body doping. Variability caused by traps and surface states, such as random telegraph noise (RTN), though less significant than RDF today, will soon be a major problem. The increased complexity of such residual-charge-induced variability due to non-Gaussian and time-dependent behavior will necessitate new approaches for variation-aware design.

Cognitive radio is an emerging technology to further improve the efficiency of spectrum use. Due to the nature of the technology, it has many facets, including its enabling technologies, its implementation issues and its regulatory implications. In ITU-R (International Telecommunications Union – Radiocommunication sector), cognitive radio systems are currently being studied so that ITU-R can have a clear picture on this new technology and its potential regulatory implications, from a viewpoint of global spectrum management. This paper introduces the recent results of the ITU-R studies on cognitive radio on both regulatory and technical aspects. This paper represents a personal opinion of the author, but not an official view of the ITU-R.

A recursive and efficient method for generating binary vectors in non-increasing order of their likelihood for a set of all binary vectors is proposed. Numerical results on experiments show the effectiveness of this method. Efficient decoding algorithms with simulation results are also proposed as applications of the method.

In this letter, a new approach to segment depth-of-field (DoF) images is proposed. The methodology is based on a two-stage model of visual neuron. The first stage is a retinal filtering by means of luminance normalizing non-linearity. The second stage is a V1-like filtering using filters estimated by independent component analysis (ICA). Segmented image is generated by the response activity of the neuron measured in terms of kurtosis. Results demonstrate that the model can discriminate image parts in different levels of depth-of-field. Comparison with other methodologies and limitations of the proposed methodology are also presented.