The past decade has seen a surge of research activities in the fields of mobile computing and wireless communication. In particular, recent technological advances have made portable devices, such as PDA, laptops, and wireless modems to be very compact and affordable. To effectively operate portable devices, energy efficiency and Quality of Service (QoS) provisioning are two primary concerns. Dynamic Voltage Scaling (DVS) is a common method for energy conservation for portable devices. However, due to the amount of data that needs to be dynamically handled in varying time periods, it is difficult to apply conventional DVS techniques to QoS sensitive multimedia applications. In this paper, a new adaptive DVS algorithm is proposed for QoS assurance and energy efficiency. Based on the repeated learning model, the proposed algorithm dynamically schedules multimedia service requests to strike the appropriate performance balance between contradictory requirements. Experimental results clearly indicate the performance of the proposed algorithm over that of existing schemes.

A low-complexity Reed-Solomon (RS) decoder design based on the modified Euclidean (ME) algorithm proposed by Truong is presented in this paper. Low complexity is achieved by reformulating Truong's ME algorithm using the proposed polynomial manipulation scheme so that a more compact polynomial representation can be derived. Together with the developed folding scheme and simplified boundary cell, the resulting design effectively reduces the hardware complexity while meeting the throughput requirements of optical communication systems. Experimental results demonstrate that the developed RS(255, 239) decoder, implemented in the TSMC 0.18 µm process, can operate at up to 425 MHz and achieve a throughput rate of 3.4 Gbps with a total gate count of 11,759. Compared to related works, the proposed decoder has the lowest area requirement and the smallest area-time complexity.

The processor-sharing (PS) rule arises as a natural paradigm in a variety of practical situations, including time-shared computer systems. Although there has been much work on Poisson-input queueing analysis for the PS rule, there have been few results for renewal-input GI/G/1 (PS) systems. We consider the GI/G/1 (PS) system to provide develop a two-moment approximation for the mean performance measures. We derive the relationship between the mean unfinished work and the conditional mean sojourn time for the GI/G/1 (PS) system. Using this relationship, we derive approximate formulas for the mean conditional sojourn time, mean sojourn time, and the mean number of customers in the GI/G/1 (PS) system. Numerical examples are presented to compare the approximation with exact and simulated results. We show that the proposed approximate formulas have good accuracy.

The aim of this study is to realize a simplified gait analysis system using wearable sensors. In this paper, a joint angle measurement method using Kalman filter to correct gyroscope signals from accelerometer signals was examined in measurement of hip, knee and ankle joint angles with a wireless wearable sensor system, in which the sensors were attached on the body without exact positioning. The lower limb joint angles of three healthy subjects were measured during gait with the developed sensor system and a 3D motion measurement system in order to evaluate the measurement accuracy. Then, 10 m walking measurement was performed under different walking speeds with a healthy subject in order to find the usefulness of the system as a simplified gait analysis system. The joint angles were measured with reasonable accuracy, and the system showed joint angle changes that were similar to those shown in a previous report as walking speed changed. It would be necessary to examine the influence of sensor attachment position and method for more stable measurement, and also to study other parameters for gait evaluation.

Modern microprocessors employ caches to bridge the great speed variance between a main memory and a central processing unit, but these caches consume a larger and larger proportion of the total power consumption. In fact, many values in a processor rarely need the full-bit dynamic range supported by a cache. The narrow-width value occupies a large portion of the cache access and storage. In view of these observations, this paper proposes an Adaptive Various-width Data Cache (AVDC) to reduce the power consumption in a cache, which exploits the popularity of narrow-width value stored in the cache. In AVDC, the data storage unit consists of three sub-arrays to store data of different widths. When high sub-arrays are not used, they are closed to save its dynamic and static power consumption through the modified high-bit SRAM cell. The main advantages of AVDC are: 1) Both the dynamic and static power consumption can be reduced. 2) Low power consumption is achieved by the modification of the data storage unit with less hardware modification. 3) We exploit the redundancy of narrow-width values instead of compressed values, thus cache access latency does not increase. Experimental results using SPEC 2000 benchmarks show that our proposed AVDC can reduce the power consumption, by 34.83% for dynamic power saving and by 42.87% for static power saving on average, compared with a cache without AVDC.

Detecting distributed anomalies rapidly and accurately is critical for efficient backbone network management. In this letter, we propose a novel anomaly detection method that uses router connection relationships to detect distributed anomalies in the backbone Internet. The proposed method unveils the underlying relationships among abnormal traffic behavior through closed frequent graph mining, which makes the detection effective and scalable.

This paper presents the development of a sound–specific vibration interface and its evaluation results by playing three commercial games with the interface. The proposed interface complements the pitfalls of existing frequency–based vibration interfaces such as vibrating headsets, mouses, and joysticks. Those interfaces may bring negative user experiences by generating incessant vibrations because they vibrate in response to certain sound frequencies. But the proposed interface which responds to only target sounds can improve user experiences effectively. The hardware and software parts of the interface are described; the structure and the implementation of a wrist pad that delivers vibration are discussed. Furthermore, we explain a sound-matching algorithm that extracts sound characteristics and a GUI-based pattern editor that helps users to design vibration patterns. The results from evaluating the performance show that the success ratio of the sound matching is over 90% at the volume of 20 dB and the delay time is around 400 msec. In the survey about user experiences, the users evaluates that the interface is more than four times effective in improving the reality of game playing than without using the vibration interfaces, and two times than the frequency–based ones.

This paper proposes an active-RC filter that achieves a wide pseudo-continuous bandwidth-tuning range and a wide gain range with fine steps using a novel switched resistor architecture. A channel-selection filter with the proposed resistor bank is designed for a multi-mode mobile-TV receiver with the 6th order Chebyshev-I topology. The bandwidth, 0.5–6 MHz with 5% steps, supports multiple mobile-TV standards with sufficient margins for process and temperature variations. The filter also accomplishes a 30-dB variable gain range with 6-dB steps, and it relaxes the dynamic range requirement of a succeeding programmable gain amplifier. The power consumption of the filter, 3.4–5.0 mW, is adjustable according to the bandwidth and the signal level. The filter was fabricated with on-chip bandwidth-calibration circuitry in 0.18-µm CMOS and occupied 0.81 mm2.

We propose an innovative and practically attainable downlink multi-cell MIMO system with distributed transmit beamforming design. The proposed system is referred to as the MIMO-MAP system which is aimed to mitigate the rank deficiency problem of those MIMO wireless channels that can not support high-order multiplexing gains. In the MIMO-MAP system, each mobile station is allowed to receive several independent data streams from multiple access points at the same time and the same frequency. To do this, a set of noise-subspace-based receive beamformers are employed to suppress the interference among the data streams from different access points. On the other hand, if we consider each receive beamformer as part of its associated wireless channel, we virtually reduce the antenna array at each receive mobile station to a single antenna. With this arrangement, we may have the transmit signal dimension high enough to pre-cancel the inter-stream-interferences at each transmit access point. As a result, the MIMO-MAP channel can be decomposed into a large number of independent subchannels which significantly increase the channel capacity.

A novel approach for detecting anomaly in visual surveillance system is proposed in this paper. It is composed of three parts: (a) a dense motion field and motion statistics method, (b) motion directional PCA for feature dimensionality reduction, (c) an improved one-class SVM for one-class classification. Experiments demonstrate the effectiveness of the proposed algorithm in detecting abnormal events in surveillance video, while keeping a low false alarm rate. Our scheme works well in complicated situations that common tracking or detection modules cannot handle.

Sender-based message logging (SBML) with checkpointing has its well-known beneficial feature, lowering highly failure-free overhead of synchronous logging with volatile logging at sender's memory. This feature encourages it to be applied into many distributed systems as a low-cost transparent rollback recovery technique. However, the original SBML recovery algorithm may no longer be progressing in some transient communication error cases. This paper proposes a consistent recovery algorithm to solve this problem by piggybacking small log information for unstable messages received on each acknowledgement message for returning the receive sequence number assigned to a message by its receiver. Our algorithm also enables all messages scheduled to be sent, but delayed because of some preceding unstable messages to be actually transmitted out much earlier than the existing ones.

This paper presents a grid-based, real-time surface modeling algorithm in which the generation of a precise 3D model is possible by considering the user's intention during the course of the spatial input. In order to create the corresponding model according to the user's input data, plausible candidates of wand traversal patterns of grid edges are defined by considering the sequential and directional characteristics of the wand input. The continuity of the connected polygonal surfaces, including the octree space partitioning, is guaranteed without the extra crack-patching algorithm and the pre-defined patterns. Furthermore, the proposed system was shown to be a suitable and effective surface generation tool for the spatial sketching system. It is not possible to implement the unusual input intention of the 3D spatial sketching system using the conventional Marching Cubes algorithm.

The Noise Shaper of a full digital amplifier overflows randomly when the Modulation Index of PWM is higher than a certain value. The clipping from the overflow produces an abrupt increase of THD+N that limits MI or the maximum output power. In this paper, we discussed the reason of NS overflow and derived the critical value of MI. We proposed a compensation method for the clipping error and optimized compensation in the audio band. The measurement results show that the proposed method can increase the maximum output power by 6.4% at a 1% THD+N condition. The compensation is more important where the power supply voltage and speaker impedance are difficult to change as that in a car stereo or mobile.

Multiple-attribute based handoff schemes suffer from instability because of the dynamic nature of attributes and the distribution of handoff procedure over candidate networks, resulting in frequent handoffs that degrade the efficiency of resource management. To alleviate such instability, a service-history based scheme was proposed but it has several improper design decisions, e.g. it considers the history factors too optimistically and employs fixed weights that are likely to distort handoff decisions. This letter proposes to improve handoff performance by considering network state along with the service history. It takes into account the network utilization to avoid the optimistic dependency on the history and adaptively determines the weight to the service history in order to adjust its effect on the handoff decision. Simulation results show that the proposed scheme optimizes the number of handoff and the dropping probability when compared with existing schemes.

In this paper, we propose precoding and power allocation strategies for full-duplex multiple input multiple output (MIMO) relays. The precoding scheme for full-duplex MIMO relays is derived based on the block diagonalization (BD) method to suppress the self-interference in the full-duplex relaying so that each relay station (RS) can receive multiple data streams from the base station (BS), while forwarding the decoded data streams to mobile stations (MS's) simultaneously. We also develop the optimal power allocation scheme for full-duplex MIMO relays. Numerical results verify that the proposed scheme provides substantial performance improvement compared with the conventional half-duplex relay (HDR), if sufficient physical isolation between the transmit and receive antennas is ensured such that the proposed full-duplex MIMO relays operate in a tolerable self-interference range.

Wireless Sensor Networks (WSNs) are gradually moving toward the adoption of clustered heterogeneous designs, incorporating a mixture of variety kinds of sensor nodes with different radio coverage and battery capacity. Compared with homogeneous networks, heterogeneous networks are able to reduce the initial cost of the network or prolong the network lifetime. The architecture and routing protocol for this type of heterogeneous WSN should be energy aware in order to prolong the lifetime of the network. However, most of the existing clustering methods consider only initial energy of the sensor nodes and ignore the non-uniform energy drainage caused by many-to-one traffic near sink and/or cluster heads in heterogeneous network environment. In this paper, we propose a new clustering method for WSN with heterogeneous node types which selects cluster heads considering not only the transmission power and residual energy of each node but also those of its adjacent nodes. Simulation experiments show that the proposed method increases network lifetime by 80% and 60% more than that of the CC and HEED, respectively.

Boosting over weak classifiers is widely used in pedestrian detection. As the number of weak classifiers is large, researchers always use a sampling method over weak classifiers before training. The sampling makes the boosting process harder to reach the fixed target. In this paper, we propose a partial derivative guidance for weak classifier mining method which can be used in conjunction with a boosting algorithm. Using weak classifier mining method makes the sampling less degraded in the performance. It has the same effect as testing more weak classifiers while using acceptable time. Experiments demonstrate that our algorithm can process quicker than [1] algorithm in both training and testing, without any performance decrease. The proposed algorithms is easily extending to any other boosting algorithms using a window-scanning style and HOG-like features.

We propose a novel method of supervised feature projection called class-distance-based discriminant analysis (CDDA), which is suitable for automatic age estimation (AAE) from facial images. Most methods of supervised feature projection, e.g., Fisher discriminant analysis (FDA) and local Fisher discriminant analysis (LFDA), focus on determining whether two samples belong to the same class (i.e., the same age in AAE) or not. Even if an estimated age is not consistent with the correct age in AAE systems, i.e., the AAE system induces error, smaller errors are better. To treat such characteristics in AAE, CDDA determines between-class separability according to the class distance (i.e., difference in ages); two samples with similar ages are imposed to be close and those with spaced ages are imposed to be far apart. Furthermore, we propose an extension of CDDA called local CDDA (LCDDA), which aims at handling multimodality in samples. Experimental results revealed that CDDA and LCDDA could extract more discriminative features than FDA and LFDA.

Locally linear embedding (LLE) is a well-known method for nonlinear dimensionality reduction. The mathematical proof and experimental results presented in this paper show that the neighborhood sizes in LLE must be smaller than the dimensions of input data spaces, otherwise LLE would degenerate from a nonlinear method for dimensionality reduction into a linear method for dimensionality reduction. Furthermore, when the neighborhood sizes are larger than the dimensions of input data spaces, the solutions to LLE are not unique. In these cases, the addition of some regularization method is often proposed. The experimental results presented in this paper show that the regularization method is not robust. Too large or too small regularization parameters cannot unwrap S-curve. Although a moderate regularization parameters can unwrap S-curve, the relative distance in the input data will be distorted in unwrapping. Therefore, in order to make LLE play fully its advantage in nonlinear dimensionality reduction and avoid multiple solutions happening, the best way is to make sure that the neighborhood sizes are smaller than the dimensions of input data spaces.

Data caching is widely known as an effective power-saving technique, in which mobile devices use local caches instead of original data placed on a server, in order to reduce the power consumption necessary for network accesses. In such data caching, a cache invalidation mechanism is important in preventing these devices from unintentionally accessing invalid data. In this paper, we propose a broadcast-based protocol for cache invalidation in a location-aware system. The proposed protocol is designed to reduce the access time required for obtaining necessary invalidation reports through broadcast media and to avoid client-side sleep fragmentation while retrieving the reports. In the proposed protocol, a Bloom filter is used as the data structure of an invalidation report, in order to probabilistically check the invalidation of caches. Furthermore, we propose three broadcast scheduling methods that are intended to achieve flexible broadcasting structured by the Bloom filter: fragmentation avoidance scheduling method (FASM), metrics balancing scheduling method (MBSM), and minimizing access time scheduling method (MASM). The broadcast schedule is arranged for consecutive accesses to geographically neighboring invalidation reports. In addition, the effectiveness of the proposed methods is evaluated by simulation. The results indicate that the MBSM and MASM achieve a high rate of performance scheduling. Compared to the FASM, the MBSM reduces the access time by 34%, while the fragmentations on the resultant schedule increase by 40%, and the MASM reduces the access time by 40%, along with an 85% increase in the number of fragmentations.