We present a method for the objective quality evaluation of noise-reduced speech in wideband speech communication services, which utilize speech with a wider bandwidth (e.g., 7 kHz) than the usual telephone bandwidth. Experiments indicate that the amount of residual noise and the distortion of speech and noise, which are quality factors, influence the perceived quality degradation of noise-reduced speech. From the results, we observe the principal relationships between these quality factors and perceived speech quality. On the basis of these relationships, we propose a method that quantifies each quality factor in noise-reduced speech by analyzing signals that can be measured and assesses the overall perceived quality of noise-reduced speech using values of these quality factors. To verify the validity of the method, we perform a subjective listening test and compare subjective quality of noise-reduced speech with its estimation. In the test, we use various types of background noise and noise-reduction algorithms. The verification results indicate that the correlation between subjective quality and its objective estimation is sufficiently high regardless of the type of background noise and noise-reduction algorithm.

In this paper, we propose a reduced-complexity radial basis function (RBF)-assisted decision-feedback equalizer (DFE)-based turbo equalization (TEQ) scheme using a novel extended fuzzy c-means (FCM) algorithm, which not only is comparable in performance to the Jacobian RBF DFE-based TEQ but also is low-complexity. Previous TEQ research has shown that the Jacobian RBF DFE TEQ considerably reduces the computational complexity with similar performance, when compared to the logarithmic maximum a posteriori (Log-MAP) TEQ. In this study, the proposed reduced-complexity RBF DFE TEQ further greatly reduces the computational complexity and is capable of attaining a similar performance in contrast to the Jacobian RBF DFE TEQ in the context of both binary phase-shift keying (BPSK) modulation and 4 quadrature amplitude modulation (QAM). With this proposal, the materialization of the RBF-assisted TEQ scheme becomes more feasible.

This study is to investigate new schemes for distributing cryptographic keys in sensor networks. Sharing a key is the very first step to realize secure communication over an untrusted network infrastructure, but commonly used cryptographic techniques cannot be employed for sensor networks due to the restriction of computational resources of sensor nodes. A practical solution to this issue is to predistribute cryptographic keys in sensor nodes before they are deployed. A focal point in this solution is the choice of keys that are assigned to a sensor node. Eschenauer et al. considered to choose keys randomly, and Chan et al. also followed the random choice approach. We consider in this paper a new approach in which keys are assigned according to a basic algebraic geometry. The performance of the proposed scheme is investigated analytically.

Phased array antennas are attractive in terms of low cost and power consumption. This paper proposes a controlling scheme based on a bisection method for phased array antennas employing phase shifters with slow switching speed, which is typical for Micro Electro Mechanical Systems (MEMS) switches. Computer simulation results, assuming the IEEE 802.11a Wireless Local Area Network (WLAN) standard, show that the proposed scheme has good gain enhancement capability in multipath fading channels.

MUSIC-based estimation of direction of arrival (DOA) using universal steering vector (USV) is experimentally studied. A four-element array antenna and a four-channel receiver are employed for the experiment. In order to improve the accuracy of DOA estimation, USV which has already included the effect of mutual coupling between array elements and effect of array elements themselves is compensated to further include the electric delay and loss of four channels in the receiver. The compensated USV (C-USV) approach proposed in this paper does not need the time-consuming measurement of array element pattern because the compensating matrix for USV is obtained by measuring the S parameters between RF input ports of the feeding cables and IF output ports of the receiver. The experimental results of MUSIC-based DOA estimation show that C-USV approach is an accurate, effective and practical method for the MUSIC-based DOA estimation.

The management of subscriptions and events is an important task in the content-based publish/subscribe system. A good management mechanism can not only produce lower matching costs to speed up the delivery of matched events to the interested subscribers but can also induce good load balancing for subscription storage. In this paper, we consider the construction of this kind of system over a peer-to-peer overlay network and propose two message-to-node mapping schemes for system management. We both analyze and simulate the performance of the proposed schemes. The simulation results show the superiority of our schemes over existing ones.

This paper proposes two traffic control schemes to support the communication quality of multimedia streaming services such as VoIP and audio/video over IEEE 802.11 wireless LAN systems. The main features of the proposed scheme are bandwidth control for each flow of the multimedia streaming service and load balancing between access points (APs) of the wireless LAN by using information of data link, network and transport layers. The proposed schemes are implemented on a Linux machine which is called the wireless traffic controller (WTC). The WTC connects a high capacity backbone network and an access network to which the APs are attached. We evaluated the performance of the proposed WTC and confirmed that the communication quality of the multimedia streaming would be greatly improved by using this technique.

IEEE 802.11 wirelesses LANs (WLANs) have been rapidly deployed in enterprises, public areas, and households. Voice-over-IP (VoIP) and similar applications are now commonly used in mobile devices over wireless networks. Recent works have improved the quality of service (QoS) offering higher data rates to support various kinds of real-time applications. However, besides the need for higher data rates, seamless handoff and load balancing among APs are key issues that must be addressed in order to continue supporting real-time services across wireless LANs and providing fair services to all users. In this paper, we introduce a novel access point (AP) with two transceivers that improves network efficiency by supporting seamless handoff and traffic load balancing in a wireless network. In our proposed scheme, the novel AP uses the second transceiver to scan and find neighboring STAs in the transmission range and then sends the results to neighboring APs, which compare and analyze whether or not the STA should perform a handoff. The initial results from our simulations show that the novel AP module is more effective than the conventional scheme and a related work in terms of providing a handoff process with low latency and sharing traffic load with neighbor APs.

This paper presents a coexistence model of IEEE 802.15.4 with IEEE 802.11b interference in fading channels and proposes two adaptive channel allocation schemes. The first avoids the IEEE 802.15.4 interference only and the second avoids both of the IEEE 802.15.4 and IEEE 802.11b interferences. Numerical results show that the proposed algorithms are effective for avoiding interferences and for maximizing network capacity since they select a channel which gives the maximum signal to noise ratio to the system.

Video surveillance systems have a huge market, as indicated by the number of installed cameras, particularly for low-power systems. In this paper, we propose a low-power quadtree video encoder for video surveillance systems. It features a low-complexity motion estimation algorithm, an application-specific ME-MC processor, a dedicated quadtree encoder engine and a processor control-based clock-gating technique. A chip capable of encoding 30 fps VGA (640480) at 80 MHz is fabricated using 0.18 µm CMOS technology. A total of 153 K gates with 558 kbits SRAM have been integrated into a 5.0 mm3.5 mm die. The power consumption is 40.87 mW at 80 MHz for VGA at 30 fps and 1.97 mW at 3.3 MHz for QCIF at 15 fps.

A tree-shellable function is a positive Boolean function which can be represented by a binary decision tree whose number of paths from the root to a leaf labeled 1 equals the number of prime implicants. In this paper, we consider the tree-shellability of DNFs with restrictions. We show that, for read-k DNFs, the number of terms in a tree-shellable function is at most k2. We also show that, for k-DNFs, recognition of ordered tree-shellable functions is NP-complete for k=4 and tree-shellable functions can be recognized in polynomial time for constant k.

This paper proposes an efficient systolic array construction method for optimal planar systolic design of the matrix multiplication. By connection network adjustment among systolic array processing element (PE), the input/output data are jumping in the systolic array for multiplication operation requirements. Various 2-D systolic array topologies, such as square topology and hexagonal topology, have been studied to construct appropriate systolic array configuration and realize high performance matrix multiplication. Based on traditional Kung-Leiserson systolic architecture, the proposed "Jumping Systolic Array (JSA)" algorithm can increase the matrix multiplication speed with less processing elements and few data registers attachment. New systolic arrays, such as square jumping array, redundant dummy latency jumping hexagonal array, and compact parallel flow jumping hexagonal array, are also proposed to improve the concurrent system operation efficiency. Experimental results prove that the JSA algorithm can realize fully concurrent operation and dominate other systolic architectures in the specific systolic array system characteristics, such as band width, matrix complexity, or expansion capability.

We analyze the MAC performance of the IEEE 802.11 DCF and 802.11e EDCA in non-saturation condition where device does not have packets to transmit sometimes. We assume that a flow is not generated while the previous flow is in service and the number of packets in a flow is geometrically distributed. In this paper, we take into account the feature of non-saturation condition in standards: possibility of transmission performed without preceding backoff procedure for the first packet arriving at the idle station. Our approach is to model a stochastic behavior of one station as a discrete time Markov chain. We obtain four performance measures: normalized channel throughput, average packet HoL (head of line) delay, expected time to complete transmission of a flow and packet loss probability. Our results can be used for admission control to find the optimal number of stations with some constraints on these measures.

Nowadays IEEE 802.11 wireless local area networks (WLANs) support multiple transmission rates. To achieve the best performance, transmitting stations adopt the various forms of automatic rate fallback (ARF). However, ARF suffers from severe performance degradation as the number of transmitting stations increases. In this paper, we propose a new rate adaptation scheme which adjusts the ARF's up/down threshold according to the channel contention level. Simulation result shows that the proposed scheme achieves fairly good performance compared with the existing schemes.

The single-hidden-layer feedforward neural networks (SLFNs) are frequently used in machine learning due to their ability which can form boundaries with arbitrary shapes if the activation function of hidden units is chosen properly. Most learning algorithms for the neural networks based on gradient descent are still slow because of the many learning steps. Recently, a learning algorithm called extreme learning machine (ELM) has been proposed for training SLFNs to overcome this problem. It randomly chooses the input weights and hidden-layer biases, and analytically determines the output weights by the matrix inverse operation. This algorithm can achieve good generalization performance with high learning speed in many applications. However, this algorithm often requires a large number of hidden units and takes long time for classification of new observations. In this paper, a new approach for training SLFNs called least-squares extreme learning machine (LS-ELM) is proposed. Unlike the gradient descent-based algorithms and the ELM, our approach analytically determines the input weights, hidden-layer biases and output weights based on linear models. For training with a large number of input patterns, an online training scheme with sub-blocks of the training set is also introduced. Experimental results for real applications show that our proposed algorithm offers high classification accuracy with a smaller number of hidden units and extremely high speed in both learning and testing.

This paper proposes novel feedforward architecture of the second-order multibit ΔΣAD modulator with single DAC-feedback topology. The ΔΣAD modulator realizes high resolution by oversampling and noise shaping techniques. However, its SNDR (Signal to Noise and Distortion Ratio) is limited by the dynamic range of the input signal and non-idealities of circuit building blocks, particularly by the harmonic distortion in amplifier circuits. A full feedforward ΔΣAD modulator structure has the signal transfer function of unity under ideal circumstances, which means that the signal swings through the loop filter become smaller compared with a feedbacked ΔΣAD modulator. Therefore, the harmonic distortion generated inside the loop filter can be significantly reduced in the feedforward structure because the effect of non-idealities in amplifiers can be suppressed when signal swing is small. Moreover, the reduction of the internal signal swings also relaxes output swing requirements for amplifiers with low supply voltage. However, in conventional feedforward ΔΣAD modulator, an analog adder is needed before quantizer, and especially in a multibit modulator, an additional amplifier is necessary to realize the summation of feedforward signals, which leads to extra chip area and power dissipation. In this paper, we propose a novel architecture of a feedforward ΔΣAD modulator which realizes the summation of feedforward signals without additional amplifier. The proposed architecture is functionally equivalent to the conventional one but with smaller chip area and lower power dissipation. We conducted MATLAB and SPICE simulations to validate the proposed architecture and modulator circuits.

Binary search tree and framed ALOHA algorithms are commonly adopted to solve the anti-collision problem in RFID systems. In this letter, the read efficiency of these two anti-collision algorithms is compared through computer simulations. Simulation results indicate the framed ALOHA algorithm requires less total read time than the binary search tree algorithm. The initial frame length strongly affects the uplink throughput for the framed ALOHA algorithm.

This paper presents a design of an asynchronous peer-to-peer half-duplex/full-duplex-selectable data-transfer system on-chip interconnected. The data-transfer method between channels is based on a 1-phase signaling scheme realized by using multiple-valued current-mode (MVCM) circuits and encoding, which performs high-speed communication. A data transmission is selectable by adding a mode-detection circuit that observes data-transmission modes; full-duplex, half-duplex and standby modes. Especially, since current sources are completely cut off during the standby mode, the power dissipation can be greatly reduced. Moreover, both half-duplex and full-duplex communication can be realized by sharing a common circuit except a signal-level conversion circuit. The proposed interface is implemented using 0.18-µm CMOS, and its performance improvement is discussed in comparison with those of the other ordinary asynchronous methods.

It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.

Various advantages of cooperative peer-to-peer networks are strongly counterbalanced by the open nature of a distributed, serverless network. In such networks, it is relatively easy for an attacker to launch various attacks such as misrouting, corrupting, or dropping messages as a result of a successful identifier forgery. The impact of an identifier forgery is particularly severe because the whole network can be compromised by attacks such as Sybil or Eclipse. In this paper, we present an identifier authentication mechanism called random visitor, which uses one or more randomly selected peers as delegates of identity proof. Our scheme uses identity-based cryptography and identity ownership proof mechanisms collectively to create multiple, cryptographically protected indirect bindings between two peers, instantly when needed, through the delegates. Because of these bindings, an attacker cannot achieve an identifier forgery related attack against interacting peers without breaking the bindings. Therefore, our mechanism limits the possibility of identifier forgery attacks efficiently by disabling an attacker's ability to break the binding. The design rationale and framework details are presented. A security analysis shows that our scheme is strong enough against identifier related attacks and that the strength increases if there are many peers (more than several thousand) in the network.