Handoff is a critical issue for stations in IEEE 802.11-based wireless networks. In order to provide Voice-over IP (VoIP) and real-time streaming applications to stations, a handoff mechanism is needed that can reduce latency and provide seamless communication. However, the IEEE802.11 handoff scheme is not appropriate to supply their quality of service (QoS), because it is based on a full-scanning approach. Full-scanning spends too much time searching for access points (APs). Therefore, various pre-scan handoff protocols such as SyncScan and DeuceScan have been proposed. They scan to find nearby APs before the station loses contact with its current AP, but the pre-scanning overhead is considerable. Our handoff mechanism reduces the delay and overhead associated with the link layer handoff by periodically scanning the channel groups.

Temporal and spatial (geographical) fluctuations, which are present in the traffic of wireless sensor networks (WSNs), have a significant affect on the transmission performance and power consumption of WSNs. Several medium access control (MAC) mechanisms have been proposed for IEEE802.15.4 cluster-based WSNs to counter the temporal and spatial traffic fluctuations. However, these mechanisms cannot always achieve simultaneous improvement in both transmission performance and power consumption. In this paper, we propose two enhanced 2-level active period control mechanisms, BI&CAP control and BI&SD&CAP control, to achieve higher system performance than conventional control mechanisms. Various computer simulation results demonstrate the effectiveness of the proposed mechanisms for WSNs with various traffic fluctuations.

In order to study the influences of contact opening speeds on arc extinction gap length characteristics, Ag contacts were operated to break DC inductive load currents from 0.1 A to 2.0 A at 14 V with contact opening speeds of 0.5 mm/s, 1 mm/s, 2 mm/s, 5 mm/s and 10 mm/s in a switching mechanism employing a stepping motor, and arc voltage waveforms were observed at each opening of the contacts. From the results, the average arc durations were determined at each current level under the respective contact opening speeds, and the average arc extinction gap lengths were calculated by multiplying the average arc duration value and the contact opening speed value. It was found that average arc durations showed no significant differences with increasing contact opening speeds. Thus, arc extinction gaps became larger at faster opening speeds in the inductive load conditions of this study.

We review recently obtained results for CMOS (Complementary Metal Oxide Semiconductor) imaging devices used in biomedical applications. The topics include dish type image sensors, deep-brain implantation devices for small animals, and retinal prosthesis devices. Fundamental device structures and their characteristics are described, and the results of in vivo experiments are presented.

This paper presents a user-calibration-free method for estimating the point of gaze (POG). This method provides a fast and stable solution for realizing user-calibration-free gaze estimation more accurately than the conventional method that uses the optical axis of the eye as an approximation of the visual axis of the eye. The optical axis of the eye can be estimated by using two cameras and two light sources. This estimation is carried out by using a spherical model of the cornea. The point of intersection of the optical axis of the eye with the object that the user gazes at is termed POA. On the basis of an assumption that the visual axes of both eyes intersect on the object, the POG is approximately estimated using the binocular 3D eye model as the midpoint of the line joining the POAs of both eyes. Based on this method, we have developed a prototype system that comprises a 19″ display with two pairs of stereo cameras. We evaluated the system experimentally with 20 subjects who were at a distance of 600 mm from the display. The root-mean-square error (RMSE) of measurement of POG in the display screen coordinate system is 1.58.

Scene-context plays an important role in scene analysis and object recognition. Among various sources of scene-context, we focus on scene-context scale, which means the effective scale of local context to classify an image pixel in a scene. This paper presents random forests based image categorization using the scene-context scale. The proposed method uses random forests, which are ensembles of randomized decision trees. Since the random forests are extremely fast in both training and testing, it is possible to perform classification, clustering and regression in real time. We train multi-scale texton forests which efficiently provide both a hierarchical clustering into semantic textons and local classification in various scale levels. The scene-context scale can be estimated by the entropy of the leaf node in the multi-scale texton forests. For image categorization, we combine the classified category distributions in each scale and the estimated scene-context scale. We evaluate on the MSRC21 segmentation dataset and find that the use of the scene-context scale improves image categorization performance. Our results have outperformed the state-of-the-art in image categorization accuracy.

Since the Content Distribution Network (CDN) and IP multicast have heavy infrastructure requirements, their deployment is quite restricted. In contrast, peer-to-peer (P2P) streaming applications are independent on infrastructures and thus have been widely deployed. Emerging wireless ad-hoc networks are poised to enable a variety of streaming applications. However, many potential problems, that are trivial in wired networks, will emerge when deploying existing P2P streaming applications directly into wireless ad-hoc networks. In this paper, we propose a goodput optimization framework for P2P streaming over wireless ad-hoc networks. A two-level buffer architecture is proposed to reassign the naive streaming systems' data requests. The framework adopts a chunk size-varying transmission algorithm to obtain smooth playback experience and acceptable overhead and utilize limited bandwidth resources efficiently. The distinguishing features of our implementation are as follows: first, the framework works as a middleware and is independent on the streaming service properties; existing P2P streaming application can be deployed in wireless ad-hoc networks with minimum modifications and development cost; second, the proposed algorithm can reduce unnecessary communication overheads compared with traditional algorithms which gain high playback continuity with small chunk size; finally, our scheme can utilize low bandwidth transmission paths rather than discarding them, and thus improve overall performance of the wireless network. We also present a set of experiments to show the effectiveness of the proposed mechanism.

Break arcs are rotated with the radial magnetic field formed by a magnet embedded in the fixed contact. They are generated in a DC42 V resistive circuit. The circuit current when the contacts are closed varies from 5 A to 21 A. The strength of a radial magnetic field for rotating break arcs changes. Arc duration is investigated. Then rotational frequency, arc length and Lorentz force when the periodic rotation of break arcs starts are analyzed to investigate the conditions required to rotate break arcs. The following results are obtained. The arc length L when the rotational motion of the break arc starts is almost constant at a constant magnetic flux density with an increase in circuit current. The arc length L decreases with an increase in the magnetic flux density of the radial magnetic field. The rotational motion of break arcs starts when the arc length L reaches a certain value determined by magnetic flux density. Rotational frequency and Lorentz force increase linearly with an increase in circuit current.

An efficient pruning method is proposed for the infinity-norm sphere decoding based on Schnorr-Euchner enumeration in multiple-input multiple-output spatial multiplexing systems. The proposed method is based on the characteristics of the infinity norm, and utilizes the information of the layer at which the infinity-norm value is selected in order to decide unnecessary sub-trees that can be pruned without affecting error-rate performance. Compared to conventional pruning, the proposed pruning decreases the average number of tree-visits by up to 37.16% in 44 16-QAM systems and 33.75% in 66 64-QAM systems.

The present study examined the evaluation of aging using the photic driving response, a measure used in routine EEG examinations. We examined 60 normal participants without EEG abnormalities, classified into three age groups (2029, 3059 and over 60 years; 20 participants per group). EEG was measured at rest and during photic stimulation (PS). We calculated Z-scores as a measure of enhancement and suppression due to visual stimulation at rest and during PS and tested for between-group and intraindividual differences. We examined responses in the alpha frequency and harmonic frequency ranges separately, because alpha suppression can affect harmonic frequency responses that overlap the alpha frequency band. We found a negative correlation between Z-scores for harmonics and age by fitting the data to a linear function (CC: -0.740). In contrast, Z-scores and alpha frequency were positively correlated (CC: 0.590).

A mobile station (MS) in an IEEE 802.16e network manages its limited energy using the sleep mode operation. An MS can power down its physical operation components during the unavailability interval of the sleep mode. To reduce energy consumption by increasing the unavailability interval, this paper proposes an enhanced power saving mechanism (ePSM) when both activated Type I and Type II power saving classes (PSCs) exist in an MS. A performance evaluation confirms that ePSM results in the improved performance in terms of the unavailability interval as well as the energy consumption than conventional schemes.

In this paper, a novel algorithm, Cross Low-dimension Pursuit, based on a new structured sparse matrix, Permuted Block Diagonal (PBD) matrix, is proposed in order to recover sparse signals from incomplete linear measurements. The main idea of the proposed method is using the PBD matrix to convert a high-dimension sparse recovery problem into two (or more) groups of highly low-dimension problems and crossly recover the entries of the original signal from them in an iterative way. By sampling a sufficiently sparse signal with a PBD matrix, the proposed algorithm can recover it efficiently. It has the following advantages over conventional algorithms: (1) low complexity, i.e., the algorithm has linear complexity, which is much lower than that of existing algorithms including greedy algorithms such as Orthogonal Matching Pursuit and (2) high recovery ability, i.e., the proposed algorithm can recover much less sparse signals than even 1-norm minimization algorithms. Moreover, we demonstrate both theoretically and empirically that the proposed algorithm can reliably recover a sparse signal from highly incomplete measurements.

In this note, we go further on the “basis exchange” idea presented in [2] by using Mobious inversion. We show that the matrix S1(f)S0(f)-1 has a nice form when f is chosen to be the majority function, where S1(f) is the matrix with row vectors υk(α) for all α ∈ 1f and S0(f)=S1(f ⊕ 1). And an exact counting for Boolean functions with maximum algebraic immunity by exchanging one point in on-set with one point in off-set of the majority function is given. Furthermore, we present a necessary condition according to weight distribution for Boolean functions to achieve algebraic immunity not less than a given number.

Silver electrical contacts are separated to generate break arcs in a DC48 V/6-24 A resistive circuit. The transverse magnetic field formed by a permanent magnet is applied to the break arcs. A series of experiments are carried out for two different experimental conditions. One condition is a constant contact separating speed while the magnetic flux density is changed to investigate the shortening effect of the arc duration. Another condition is a constant magnetic flux density while the contact separating speed is changed to investigate the changes in the arc duration and the contact gap when the break arc is extinguished. As a result, with constant separating speed, it is confirmed that the duration of break arcs is shortened by the transverse magnetic field and the break arcs are extinguished when the arc length reaches a certain value L. Under the condition of constant transverse magnetic field, (i) the arc duration is shortened by increasing the separation speed; (ii) the contact gap when the break arc is extinguished is almost constant when the separating speed v is sufficiently faster than 5 mm/s.

With energy shortages and global climate change leading our concerns these days, the energy consumption of datacenters has become a key issue. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This paper aims at designing, implementing and evaluating a Green Scheduler for reducing energy consumption of datacenters in Cloud computing platforms. It is composed of four algorithms: prediction, ON/OFF, task scheduling, and evaluation algorithms. The prediction algorithm employs a neural predictor to predict future load demand based on historical demand. According to the prediction, the ON/OFF algorithm dynamically adjusts server allocations to minimize the number of servers running, thus minimizing the energy use at the points of consumption to benefit all other levels. The task scheduling algorithm is responsible for directing request traffic away from powered-down servers and toward active servers. The performance is monitored by the evaluation algorithm to balance the system's adaptability against stability. For evaluation, we perform simulations with two load traces. The results show that the prediction mode, with a combination of dynamic training and dynamic provisioning of 20% additional servers, can reduce energy consumption by 49.8% with a drop rate of 0.02% on one load trace, and a drop rate of 0.16% with an energy consumption reduction of 55.4% on the other. Our method is also proven to have a distinct advantage over its counterparts.

Distributed systems desire to construct a random overlay graph for robustness, efficient information dissemination and load balancing. A random walk-based overlay construction is a promising alternative to generate an ideal random scale free overlay in distributed systems. However, a simple random walk-based overlay construction can be affected by node churn. Especially, the number of edges increases and the degree distribution is skewed. This inappropriate distortion can be exploited by malicious nodes. In this paper, we propose a modified random walk-based overlay construction supported by a logistic/trial based decision function to compensate the impact of node churn. Through event-driven simulations, we show that the decision function helps an overlay maintain the proper degree distribution, low diameter and low clustering coefficient with shorter random walks.

In this article, we first review key derivation functions specified in NIST SP 800-108 and one proposed by Krawczyk. Then, we propose parallelizable key derivation functions obtained by modifying or using the existing schemes. We also define two measures of efficiency of key derivation functions, and evaluate their performance in terms of the two measures.

In this paper, we study the problem of efficient processing of conjunctive queries in Peer-to-Peer systems based on Distributed Hash Tables (P2P DHT, for short). The basic idea of our approach is to cache the search result for the queries submitted in the past, and to use them to improve the performance of succeeding query processing. More concretely, we propose to adopt Bloom filters as a concrete implementation of such a result cache rather than a list of items used in many conventional schemes. By taking such an approach, the cache size for each conjunctive query becomes as small as the size of each file index. The performance of the proposed scheme is evaluated by simulation. The result of simulation indicates that the proposed scheme is particularly effective when the size of available memory in each peer is bounded by a small value, and when the number of peers is 100, it reduces the amount of data transmissions of previous schemes by 75%.

In this paper, we present an approach of detecting speech presence for which the decision rule is based on a combination of multiple features using a sigmoid function. A minimum classification error (MCE) training is used to update the weights adjustment for the combination. The features, consisting of three parameters: the ratio of ZCR, the spectral energy, and spectral entropy, are combined linearly with weights derived from the sub-band domain. First, the Bark-scale wavelet decomposition (BSWD) is used to split the input speech into 24 critical sub-bands. Next, the feature parameters are derived from the selected frequency sub-band to form robust voice feature parameters. In order to discard the seriously corrupted frequency sub-band, a strategy of adaptive frequency sub-band extraction (AFSE) dependant on the sub-band SNR is then applied to only the frequency sub-band used. Finally, these three feature parameters, which only consider the useful sub-band, are combined through a sigmoid type function incorporating optimal weights based on MSE training to detect either a speech present frame or a speech absent frame. Experimental results show that the performance of the proposed algorithm is superior to the standard methods such as G.729B and AMR2.

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.