RAKE receivers are generally employed to collect multipath energy in single-carrier ultra-wideband (SC-UWB) systems and direct-sequence ultra-wideband (DS-UWB) systems. Performance of RAKE receivers in these two kinds of systems is studied and compared with each other in this letter. Both theoretical analysis and simulation results over IEEE 802.15.3a UWB channels are presented. Our results show that, with the same signal to noise ratio (SNR) per bit, the same occupied bandwidth and the same number of RAKE fingers, RAKE receivers with maximum ratio combination (MRC) in SC-UWB systems can achieve exactly the same performance as that in DS-UWB systems.

An implantable WBAN path-loss model for a capsule endoscopy which is used for examining digestive organs, is developed by conducting simulations and experiments. First, we performed FDTD simulations on implant WBAN propagation by using a numerical human model. Second, we performed FDTD simulations on a vessel that represents the human body. Third, we performed experiments using a vessel of the same dimensions as that used in the simulations. On the basis of the results of these simulations and experiments, we proposed the gradient and intercept parameters of the simple path-loss in-body propagation model.

In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

We propose a proof-of-concept of a switchable multi-frequency MMIC (monolithic microwave integrated circuit) oscillator device, operating in the 60 GHz millimeter wave band, which is implemented in GaAs p-HEMT transistor technology. Oscillators that can switch between two frequencies have been designed, fabricated and evaluated. The oscillator uses a cross-coupled FET topology, combined with a bent asymmetric coplanar stripline for the resonator, and a switched-capacitor for the frequency switching components. The oscillator generates two oscillations at f/2 and f where f is the target frequency of around 60 GHz. The switchable oscillator has been demonstrated for the range of frequency from 44 GHz to 68.9 GHz. Moreover, the designed oscillator exhibits a wide-band negative resistance property that allows fabricating switchable oscillators covering the 50 to 75 GHz V-band. An evaluated switchable oscillator delivers -17.09 dBm and -13.72 dBm output power at 62.45 GHz and 64.78 GHz, for a supplied power of 40.6 mW and 39.1 mW, respectively.

In this letter, a statistical uncorrelated near class discriminant (SUNCD) approach is proposed for face recognition. The optimal discriminant vector obtained by this approach can differentiate one class and its near classes, i.e., its nearest neighbor classes, by constructing the specific between-class and within-class scatter matrices and using the Fisher criterion. In this manner, SUNCD acquires all discriminant vectors class by class. Furthermore, SUNCD makes every discriminant vector satisfy locally statistical uncorrelated constraints by using the corresponding class and part of its most neighboring classes. Experiments on the public AR face database demonstrate that the proposed approach outperforms several representative discriminant methods.

This paper presents an integer discrete cosine transform (IntDCT) with only dyadic values such as k/2n (k, n∈ in N). Although some conventional IntDCTs have been proposed, they are not suitable for lossless-to-lossy image coding in low-bit-word-length (coefficients) due to the degradation of the frequency decomposition performance in the system. First, the proposed M-channel lossless Walsh-Hadamard transform (LWHT) can be constructed by only (log2M)-bit-word-length and has structural regularity. Then, our 8-channel IntDCT via LWHT keeps good coding performance even if low-bit-word-length is used because LWHT, which is main part of IntDCT, can be implemented by only 3-bit-word-length. Finally, the validity of our method is proved by showing the results of lossless-to-lossy image coding in low-bit-word-length.

Major challenges of the conventional spread-transform dither modulation (STDM) watermarking approach are two-fold: (i) it exploits a fixed watermarking strength (more particularly, the quantization index step size) to the whole cover image; and (ii) it is fairly vulnerable to the amplitude changes. To tackle the above challenges, an adaptive spread-transform dither modulation (ASTDM) approach is proposed in this paper for conducting robust color image watermarking by incorporating a new perceptual model into the conventional STDM framework. The proposed approach exploits a new perceptual model to adjust the quantization index step sizes according to the local perceptual characteristics of a cover image. Furthermore, in contrast to the conventional Watson's model is vulnerable to the amplitude changes, our proposed new perceptual model makes the luminance masking thresholds be consistent with any amplitude change, while keeping the consistence to the properties of the human visual system. In addition, certain color artifacts could be incurred during the watermark embedding procedure, since some intensity values are perceptibly changed to label the watermark. For that, a color artifact suppression algorithm is proposed by mathematically deriving an upper bound for the intensity values according to the inherent relationship between the saturation and the intensity components. Extensive experiments are conducted using 500 images selected from Corel database to demonstrate the superior performance of the proposed ASTDM approach.

This letter suggests an opportunistic resource scheduling scheme for supporting users with variety of services in wireless network. This scheme is designed to increase resource utilization while meeting diverse quality of service (QoS) requirements. It can be achieved by considering the channel status and the urgency for QoS support synthetically.

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

This paper proposes a method to generate alternative scenarios from a normal scenario written with a scenario language. This method includes (1) generation of alternative plans and (2) generation of alternative scenario by a user's selection of these plans. The proposed method enables users to decrease the omission of the possible alternative scenarios in the early stages of development. The method will be illustrated with some examples.

Moment invariants of a discrete image are not strictly invariant to image displacements due to quantization errors. This letter introduces a weighting function such that the pixel value is smoothly reduced to zero at the boundary of the image. Image moments of the weighted image are robust against quantization errors, and the moment invariants of the weighted image are more invariant than those of the unweighted image.

The Burst ACK scheme enhances effective throughput by reducing ACK overhead when a transmitter sends sequentially multiple data frames to a destination. IEEE 802.11e is one such example. The size of the data frame body and the number of burst data frames are important burst transmission parameters that affect throughput. The larger the burst transmission parameters are, the better the throughput under error-free conditions becomes. However, large data frame could reduce throughput under error-prone conditions caused by signal-to-noise ratio (SNR) deterioration. If the throughput can be calculated from the burst transmission parameters and error rate, the appropriate ranges of the burst transmission parameters could be narrowed down, and the necessary buffer size for storing transmit data or received data temporarily could be estimated. In this paper, we present a method that features a simple algorithm for estimating the effective throughput from the burst transmission parameters and error rate. The calculated throughput values agree well with the measured ones for actual wireless boards based on the IEEE 802.11-based original MAC protocol. We also calculate throughput values for larger values of the burst transmission parameters outside the assignable values of the wireless boards and find the appropriate values of the burst transmission parameters.

Introducing adaptive online data compression at network-internal nodes is considered for alleviating traffic congestion on the network. In this paper, we assume that advanced relay nodes, which possess both a relay function (network resource) and a processing function (computational and storage resources), are placed inside the network, and we propose an adaptive online lossless packet compression scheme utilized at these nodes. This scheme selectively compresses a packet according to its waiting time in the queue during congestion. Through preliminary investigation using actual traffic datasets, we investigate the compression ratio and processing time of packet-by-packet compression in actual network environments. Then, by means of computer simulations, we show that the proposed scheme reduces the packet delay time and discard rate and investigate factors necessary in achieving efficient packet relay.

Estimating the conditional mean of an input-output relation is the goal of regression. However, regression analysis is not sufficiently informative if the conditional distribution has multi-modality, is highly asymmetric, or contains heteroscedastic noise. In such scenarios, estimating the conditional distribution itself would be more useful. In this paper, we propose a novel method of conditional density estimation that is suitable for multi-dimensional continuous variables. The basic idea of the proposed method is to express the conditional density in terms of the density ratio and the ratio is directly estimated without going through density estimation. Experiments using benchmark and robot transition datasets illustrate the usefulness of the proposed approach.

A simple suboptimal power allocation method is proposed for SC-FDMA systems. It is known that the performance of constant power-based allocation methods is close to that of optimal solutions. In this letter, by utilizing the waterfilling condition inequality derived for SC-FDMA systems, a threshold is set to select subcarriers for loading constant power to these selected subcarriers. It offers competitive performance as confirmed by the simulation results.

Human detection has witnessed significant development in recent years. The introduction of cascade structure and integral histogram has greatly improved detection speed. But real-time detection is still only possible for sparse scan of 320 240 sized images. In this work, we propose a matrix-based structure to reorganize the computation structure of window-scanning detection algorithms, as well as a new pre-processing method called Hierarchical HOG Matrices (HHM) in place of integral histogram. Our speed-up scheme can process 320 240 sized images by dense scan (≈ 12000 windows per image) at the speed of about 30 fps, while maintaining accuracy comparable to the original HOG + cascade method.

Dynamic Voltage Scaling (DVS) is a well-known low-power design technique, which adjusts the clock speed and supply voltage dynamically to reduce the energy consumption of real-time systems. Previous studies considered the probabilistic distribution of tasks' workloads to assist DVS in task scheduling. These studies use probability information for intra-task frequency scheduling but do not sufficiently explore the opportunities for the system workload to save more energy. This paper presents a novel DVS algorithm for periodic real-time tasks based on the analysis of the system workload to reduce its power consumption. This algorithm takes full advantage of the probabilistic distribution characteristics of the system workload under priority-driven scheduling such as Earliest-Deadline-First (EDF). Experimental results show that the proposed algorithm reduces processor idle time and spends more busy time in lower-power speeds. The measurement indicates that compared to the relative DVS algorithms, this algorithm saves energy by at least 30% while delivering statistical performance guarantees.

In this letter, we present a route discovery protocol for ad hoc multi-hop cellular networks which uses directional information towards the base station. The proposed protocol, based on the reactive approach, reduces flooding as much as possible. To quantify this, we analyze its performance in terms of how much progress it makes per hop and how much reduction in routing packet number it achieves per route discovery. The analytical, as well as simulation, results demonstrate that the proposed protocol significantly reduces flooding overheads and finds a route to the base station in a robust manner.

This paper investigates whether the self-heating effect in short intra-block wires will become apparent with technology scaling. These wires seem to have good thermal radiation characteristics, but we validate that the self-heating effect in local signal wires will be greater than that in optimal repeater-inserted global wires. Our numerical experiment shows that the maximum temperature increase from the silicon junction temperature will reach 40.4 in a steady state at a 14-nm process. Our attribution analysis also demonstrates that miniaturizing the area of wire cross-section exacerbates self-heating as well as using low-κ material and increased power dissipation in advanced technologies below 28 nm. It is revealed that the impact of self-heating on performance in local wires is limited, while underestimating the temperature may cause an unexpected reliability failure.

We propose two methods for avoiding the checkerboard distortion which is caused by finite word length error. The first method derives the bit length of filter coefficients required for avoiding the checkerboard distortion under a certain word length. In the second method, the checkerboard distortion can be avoided by using the cascade structure which consists of zero-hold kernel and a time-invariant filter factorized from a filter with structure for avoiding the checkerboard distortion under linear systems. It is demonstrated by simulations that we can avoid the checkerboard distortion by using these proposed methods.