The first part of this paper contains an introduction to Bell inequalities and Tsirelson's theorem for the non-specialist. The next part gives an explicit optimum construction for the "hard" part of Tsirelson's theorem. In the final part we describe how upper bounds on the maximal quantum violation of Bell inequalities can be obtained by an extension of Tsirelson's theorem, and survey very recent results on how exact bounds may be obtained by solving an infinite series of semidefinite programs.

Fair allocation of bandwidth and maximization of channel utilization are two important issues when designing a contention-based wireless medium access control (MAC) protocol. However, fulfilling both design goals at the same time is very difficult. Considering the problem in the IEEE 802.11 wireless local area networks (WLANs), in this work we propose a method using a p-persistent enhanced DCF, called P-IEEE 802.11 DCF, to achieve weighted fairness and efficient channel utilization among multiple priority classes in a WLAN. Its key idea is that when the back-off timer of a node reaches zero, the transmission probability is properly controlled to reflect the relative weights among data traffic flows so as to maximize the aggregate throughput and to minimize the frame delay at the same time. In particular, we obtain the optimal transmission probability based on a theoretical analysis, and also provide an approximation to this probability. The derived optimal and approximation are all evaluated numerically and simulated with different scenarios. The results show that the proposed method can fulfill our design goals under different numbers of priority classes and different numbers of nodes.

This paper proposes a novel service configuration approach that can realize dynamic critical Quality of Service (QoS) adaptation to ever-changing and resource-limited ubiquitous computing environments. In the approach, service configuration is reduced to a Fuzzy Control System (FCS) which aims to achieve critical QoS variations on minimal level with less power cost. Two configuration strategies, service chain reconfiguration and QoS parameters adjustment, along with a configuration algorithm, are implemented to handle different types of QoS variations. A self-optimizing algorithm is designed to enhance the adaptation of the FCS. Simulation results validate the proposed approach.

As we scale toward nanometer technologies, the increase in interconnect parameter variations will bring significant performance variability. New design methodologies will emerge to facilitate construction of reliable systems from unreliable nanometer scale components. Such methodologies require new performance models which accurately capture the manufacturing realities. In this paper, we present a Linear Fractional Transform (LFT) based model for interconnect parametric uncertainty. The new model formulates the interconnect parametric uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) and Linear Matrix Inequalities (LMI's), the porposed model reduces the order of the original interconnect network while preserves the stability. The LFT based new model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) generated from Lur'e equations. In case of large number of uncertain parameters, the new model may be applied successively: the uncertain parameters are partitioned into groups, and with regard to each group, LFT based model is applied in turns.

This paper proposes a novel dependable SRAM with 7T/14T memory cells, and introduces a new concept, "quality of a bit (QoB)" for it. The proposed SRAM has three modes: a normal mode, high-speed mode, and dependable mode, and dynamically scales its reliability, power and speed by combining two memory cells for one-bit information (i.e. 14 T/bit). By carrying out Monte Carlo simulation in a 65-nm process technology, the minimum voltages in read and write operations are improved by 0.21 V and 0.26 V, respectively, with a bit error rate of 10-8 kept. In addition, we confirm that the dependable mode achieves a lower bit error rate than the error correction code (ECC) and multi module redundancy (MMR). Furthermore, we propose a new memory array structure to avoid the half-selection problem in a write operation. The respective cell area overheads in the normal mode are 26% and 11% in the cases where additional transistors are pMOSes and nMOSes, compared to the conventional 6T memory cell.

In this paper, we propose a distance-based howling canceller with high speech quality. We have developed a distance-based howling canceller that uses only distance information by noticing the property that howling occurs according to the distance between a loudspeaker and a microphone. This method estimates the distance by transmitting a pilot signal from the loudspeaker to the microphone. Multiple frequency candidates for each howling are computed from the estimated distance and eliminated by cascading notch filters that have nulls at them. However degradation of speech quality occurs at the howling canceller output. The first cause is a shot noise occurrence at the beginning and end of the pilot signal transmission due to the discontinuous change of the amplitude. We thus develop a new pilot signal that is robust against ambient noises. We can then reduce the shot noise effect by taking the amplitude small. The second one is a speech degradation caused from overlapped stopbands of the notch filters. We thus derive a condition on the bandwidths so that stopbands do not overlap, and propose an adaptive bandwidth scheme which changes the bandwidth according to the distance.

It is a tedious and subjective task to measure severity of a dysarthria by manually evaluating his/her speech using available standard assessment methods based on human perception. This paper presents an automated approach to assess speech quality of a dysarthric speaker with cerebral palsy. With the consideration of two complementary factors, speech consistency and speech distinction, a speech quality indicator called speech clarity index (Ψ) is proposed as a measure of the speaker's ability to produce consistent speech signal for a certain word and distinguished speech signal for different words. As an application, it can be used to assess speech quality and forecast speech recognition rate of speech made by an individual dysarthric speaker before actual exhaustive implementation of an automatic speech recognition system for the speaker. The effectiveness of Ψ as a speech recognition rate predictor is evaluated by rank-order inconsistency, correlation coefficient, and root-mean-square of difference. The evaluations had been done by comparing its predicted recognition rates with ones predicted by the standard methods called the articulatory and intelligibility tests based on the two recognition systems (HMM and ANN). The results show that Ψ is a promising indicator for predicting recognition rate of dysarthric speech. All experiments had been done on speech corpus composed of speech data from eight normal speakers and eight dysarthric speakers.

In this paper, we propose a rate control technique for H.264/AVC using subjective quality of video for off line video coding. We propose to use Video Quality Metric (VQM) with an evolution strategy algorithm, which is capable of identifying the best possible quantization parameters for each frame/macroblock to encode the video sequence such that it would maximize the subjective quality of the entire video sequence subjected to the target bit rate. Simulation results suggest that the proposed technique can improve the RD performance of the H.264/AVC codec significantly. With the proposed technique, up to 40% bit rate reduction can be achieved at the same video quality. Furthermore, results show that the proposed technique can improve the subjective quality of the encoded video significantly for video sequences especially with high motion.

A novel automatic quality factor (Q) tuning scheme for an low-power and wideband active-RC filter is presented. Although Q-tuning is effective to reduce the power consumption of wideband active-RC filters, there are several problems since the Q-tuning normally relies on a magnitude locked loop (MLL). MLL is not accurate due to the amplitude detection circuits, and occupied area and power consumption tends to be large due to its complexity. In addition, flexibility to the reference signal may be the problem, since the reference signal which has a fixed accurate frequency is required. In order to solve these problems, we propose a Q-tuning scheme, which does not require a MLL. Therefore, proposed Q-tuning scheme has good accuracy, small die area, low power consumption and flexibility to the reference signal. In our proposed scheme, Q is tuned by adjusting the phase of an integrator to 90 degrees. The phase of an integrator is adjusted by detecting and controlling the oscillation frequency of a two-stage ring-integrator to the cutoff frequency of a filter, since the phase shift of an integrator is exactly 90 degrees at the oscillation frequency. The frequency is easily detected and controlled by counters and variable resistors, respectively. The Q-tuning circuit with a 5th-order Chebyshev LPF is implemented in a 0.13 µm CMOS technology. The tuning circuit occupies 0.12 mm2 and consumes 2.6 mW from 1.2 V supply.

In this paper, we propose an Adaptation Decision-Taking Engine (ADTE) that targets the delivery of scalable video content in mobile usage environments. Our ADTE design relies on an objective perceptual quality metric in order to achieve video adaptation according to human visual perception, thus allowing to maximize the Quality of Service (QoS). To describe the characteristics of a particular usage environment, as well as the properties of the scalable video content, MPEG-21 Digital Item Adaptation (DIA) is used. Our experimental results show that the proposed ADTE design provides video content with a higher subjective quality than an ADTE using the conventional maximum-bit-allocation method.

This paper proposes the sliding mode control using LMI techniques and adaptive recurrent fuzzy neural network (RFNN) for a class of uncertain nonlinear time-delay systems. First, a novel TS recurrent fuzzy neural network (TS-RFNN) is developed to provide more flexible and powerful compensation of system uncertainty. Then, the TS-RFNN based sliding model control is proposed for uncertain time-delay systems. In detail, sliding surface design is derived to cope with the non-Isidori-Bynes canonical form of dynamics, unknown delay time, and mismatched uncertainties. Based on the Lyapunov-Krasoviskii method, the asymptotic stability condition of the sliding motion is formulated into solving a Linear Matrix Inequality (LMI) problem which is independent on the time-varying delay. Furthermore, the input coupling uncertainty is also taken into our consideration. The overall controlled system achieves asymptotic stability even if considering poor modeling. The contributions include: i) asymptotic sliding surface is designed from solving a simple and legible delay-independent LMI; and ii) the TS-RFNN is more realizable (due to fewer fuzzy rules being used). Finally, simulation results demonstrate the validity of the proposed control scheme.

With the popularity of BitTorrent-like P2P applications, improving its performance has been an active research area. Super-seeding, a special upload policy for the initial seeder, improves the efficiency in producing multiple seeds and reduces the uploading bytes of content initiators, thus being highly expected as a promising solution for improving downloading performance while decreasing uploading cost. However, the overall impacts of super seeding upon BitTorrent performance remain a question and have not been analyzed so far in literature. In this paper, we present an analytical and experimental study over the performance of super-seeding scheme. We attempt to answer the following questions: whether and how much super-seeding saves uploading cost, whether the overall downloading time is decreased by super-seeding, and in which circumstances super-seeding performs worse. Based on the seeding process, our analytical study gives formulas on the new piece distribution time, average downloading time and minimum distribution time for heterogeneous P2P file distribution system with super-seeding. Robust evidence supporting the use (or not) of super-seeding is given based on our worldwide Internet experiments over wide distribution of 250 PlanetLab nodes. With a well-designed experimental scenario, we study the overall download time and upload cost of super seeding scheme under varying seed bandwidth and peer behavior. Results show that super-seeding can save an upload ratio of 20% and does help speeding up swarms in certain modes. Tentative conclusions about the effectiveness of super-seeding and its optimal working circumstances are given with inside mechanism analyzed and negative factor identified. Our work not only provides reference for the potential adoption of super-seeding in BitTorrent and other P2P applications, but also much insights for the tussle of enhancing of Quality of Experience (QoE) and saving cost for a large-scale BitTorrent-like P2P commercial application.

This work proposes new features to improve the pathological voice quality classification performance. They are the means, the variances, and the perturbations of the higher-order statistics (HOS) such as the skewness and the kurtosis. The HOS-based features show meaningful differences among normal, grade 1, grade 2, and grade 3 voices classified in the GRBAS scale. The jitter, the shimmer, the harmonic-to-noise ratio (HNR), and the variance of the short-time energy are utilized as the conventional features. The performances are measured by the classification and regression tree (CART) method. Specifically, the CART-based method by utilizing both the conventional features and the HOS-based ones shows its effectiveness in the pathological voice quality measurement, with the classification accuracy of 87.8%.

A feature of services provided in a Next Generation Network (NGN) is that the end-to-end quality is guaranteed. This is quite a challenging issue, given the considerable fluctuation in network conditions within a Fixed Mobile Convergence (FMC) network. Therefore, a novel approach, whereby a network node and a mobile terminal such as a cellular phone cooperate with each other to control service quality is essential. In order to achieve such cooperation, the mobile terminal needs to become more intelligent so it can estimate the service quality, including the user's perceptual quality, and notify the measurement result to the network node. Subsequently, the network node implements some kind of service control function, such as a resource and admission control function, based on the notification from the mobile terminal. In this paper, the role of the mobile terminal in such collaborative system is focused on. As a part of a QoS/QoE measurement system, we describe an objective speech quality assessment with payload discrimination of lost packets to measure the user's perceptual quality of VoIP. The proposed assessment is so simple that it can be implemented on a cellular phone. We therefore did this as part of the QoS/QoE measurement system. By using the implemented system, we can measure the user's perceptual quality of VoIP as well as the network QoS metrics, in terms of criteria such as packet loss rate, jitter and burstiness in real time.

In real-time embedded systems, there is requirement for adapting both energy consumption and Quality of Services (QoS) of tasks according to their importance. This paper proposes an adaptive power-aware resource allocation method to resolve a trade-off between the energy consumption and QoS levels according to their importance with guaranteeing fairness. The proposed resource allocator consists of two components: the total resource optimizer to search for the optimal total resource and QoS-fairness-based allocator to allocate resource to tasks guaranteeing the fairness. These components adaptively achieve the optimal resource allocation formulated by a nonlinear optimization problem with the time complexity O(n) for the number of tasks n even if tasks' characteristics cannot be identified precisely. The simulation result shows that the rapidness of the convergence of the resource allocation to the optimal one is suitable for real-time systems with large number of tasks.

In video streaming applications over the Internet, TCP-friendly rate control schemes are useful for improving network stability and inter-protocol fairness. However, they do not always guarantee a smooth video streaming. To simultaneously satisfy both the network and user requirements, video streaming applications should be quality-adaptive. In this paper, we propose a new quality adaptation mechanism to adjust the quality of congestion-controlled video stream by controlling the frame rate. Based on the current network condition, it controls the frame rate of video stream and the sending rate in a TCP-friendly manner. Through a simulation, we prove that our adaptation mechanism appropriately adjusts the quality of video stream while improving network stability.

To guarantee the timely provisioning of QoS to real-time oriented multiparty and distributed computing applications (e.g., video conferencing and grid computing) that require the utilization of time and quantity-related resources, the resource should be reserved in advance. However, this new type of reservation (i.e., advance reservation) may collide with legacy (i.e., immediate) reservations that do not specify their session duration. In this paper, to suggest a balanced solution between sharing pools of resources and the managing of collisions between reservation calls, a revenue-based resource sharing scheme (focusing on the bandwidth) is proposed. The proposed scheme attempts to avoid possible collisions by employing a virtual profile of resources reserved in advance in an effort to achieve enhanced resource utilization. It is shown through NS-2 [22] -based network simulations that the proposed scheme can achieve balanced performance when compared with other schemes, including static resource partitioning and complete resource sharing.

Design by Contract (DBC), originated in the Eiffel programming language, is generally accepted as a practical method for building reliable software. Currently, however, few languages have built-in support for it. In recent years, several methods have been proposed to support DBC in Java. We compare eleven DBC tools for Java by analyzing their impact on the developer's programming activities, which are characterized by seven quality attributes identified in this paper. It is shown that each of the existing tools fails to achieve some of the quality attributes. This motivates us to develop ezContract, an open source DBC tool for Java that achieves all of the seven quality attributes. ezContract achieves streamlined integration with the working environment. Notably, standard Java language is used and advanced IDE features that work for standard Java programs can also work for the contract-enabled programs. Such features include incremental compilation, automatic refactoring, and code assist.

To fully utilize the limited battery energy of mobile electronic devices, we propose an adaptive adjustment method of processing quality for multiple image stream tasks running with widely varying execution times. This adjustment method completes the worst-case executions of the tasks with a given budget of energy, and maximizes the total reward value of processing quality obtained during their executions by exploiting the probability distribution of task execution times. The proposed method derives the maximum reward value for the tasks being executable with arbitrary processing quality, and near maximum value for the tasks being executable with a finite number of processing qualities. Our evaluation on a prototype system shows that the proposed method achieves larger reward values, by up to 57%, than the previous method.

This paper performs application-level QoS and user-level QoS assessment of audio-video streaming in cross-layer designed wireless ad hoc networks. In order to achieve high QoS at the user-level, we employ link quality-based routing in the network layer and media synchronization control in the application layer. We adopt three link quality-based routing protocols: OLSR-SS (Signal Strength), AODV-SS, and LQHR (Link Quality-Based Hybrid Routing). OLSR-SS is a proactive routing protocol, while AODV-SS is a reactive one. LQHR is a hybrid protocol, which is a combination of proactive and reactive routing protocols. For application-level QoS assessment, we performed computer simulation with ns-2 where an IEEE 802.11b mesh topology network with 24 nodes was assumed. We also assessed user-level QoS by a subjective experiment with 30 assessors. From the assessment results, we find AODV-SS the best for networks with long inter-node distances, while LQHR outperforms AODV-SS for short inter-node distances. In addition, we also examine characteristics of the three schemes with respect to the application-level QoS in random topology networks.