Optimal head related transfer functions for hearing and monaural localization in elevation: a signal processing design perspective

Localization of sound sources by human listeners has been widely studied and theories and various models of the localization and hearing mechanism have been constructed. In the classical "duplex" theory, sound localization in azimuth is explained by interaural time or equivalently, phase differences at low frequencies, and by interaural amplitude differences at higher frequencies. Head related transfer functions (HRTF's) present a linear system approach to modeling localization by representing the direction-dependent transformation the sound undergoes at each ear. Localization in elevation is explained by directional differences in the HRTF's, which also explains monaural localization. We conjecture that the HRTF's evolved during the course of nature (due to the evolution of the shape and structure of the ear etc.) are optimal with respect to several physically realizable criteria. In this paper, we investigate the problem of defining the design constraints which when optimized yield a set of HRTF's for hearing and monaural vertical localization in an attempt to better understand, and if possible, duplicate nature's design. We pursue an engineer's design perspective and formulate a constrained optimization problem, where the desired set of HRTF's is optimized according to a cost function based on several criteria for localization, hearing and smoothness, and also by imposing physically realizable constraints on the HRTF's such as nonnegativity, energy etc. The value of the cost function for a candidate set of HRTF's is an indication of the similarity of that set of HRTF's with respect to the ideal solution (measured HRTF data). The final optimization results we present are similar to the actual HRTF's measured in human subjects, and the associated cost function values are found to be almost equal. This points to the fact that the optimization criteria defined are quite relevant. The significant outcome of this research is the identification of a relevant set of mathematical criteria that could be optimized in the human auditory system to facilitate good hearing and localization. These criteria along with the associated constraints represent the desirable characteristics of the HRTF's in an HRTF-based localization system, and could lead to a better understanding and modeling of the auditory system.     

基于路由器反馈拥塞控制机制的研究

随着网络的不断发展,传统的TCP拥塞控制机制已经不能很好地适应现有的网络环境;文中在分析了不同反馈信息的价值的基础上提出了一种新的基于路由器反馈的拥塞控制机制RSCP,部署方便,不需要额外包头;该机制创造性地提出了信号包的方法与路由器交换信息,并以公平带宽和公平剩余带宽为反馈信息,在以公平带宽为基点的基础上根据公平剩余带宽的变化调整发送速率,同时采用快速启动机制使连接能够快速达到公平带宽;仿真实验证明RSCP在单瓶颈网络中能取得高利用率、低队列长度和零丢包以及良好的收敛性能.     

Delay‐dependent LMI condition for global asymptotic stability of discrete‐time uncertain state‐delayed systems using quantization/overflow nonlinearities

A delay‐dependent criterion for the global asymptotic stability of a class of uncertain discrete‐time state‐delayed systems using various combinations of quantization and overflow nonlinearities is presented. The proposed criterion is in the form of a linear matrix inequality and, hence, computationally tractable. A numerical example highlighting the usefulness of the proposed criterion is given. Copyright © 2010 John Wiley & Sons, Ltd.     

Two stage emotion recognition based on speaking rate

This paper proposes two stage speech emotion recognition approach using speaking rate. The emotions considered in this study are anger, disgust, fear, happy, neutral, sadness, sarcastic and surprise. At the first stage, based on speaking rate, eight emotions are categorized into 3 broad groups namely active (fast), normal and passive (slow). In the second stage, these 3 broad groups are further classified into individual emotions using vocal tract characteristics. Gaussian mixture models (GMM) are used for developing the emotion models. Emotion classification performance at broader level, based on speaking rate is found to be around 99% for speaker and text dependent cases. Performance of overall emotion classification is observed to be improved using the proposed two stage approach. Along with spectral features, the formant features are explored in the second stage, to achieve robust emotion recognition performance in case of speaker, gender and text independent cases.     

Buffer Management for Colored Packets with Deadlines

We consider buffer management of unit packets with deadlines for a multi-port device with reconfiguration overhead. The goal is to maximize the throughput of the device, i.e., the number of packets delivered by their deadline. For a single port or with free reconfiguration, the problem reduces to the well-known packets scheduling problem, where the celebrated earliest-deadline-first (EDF) strategy is optimal 1-competitive. However, EDF is not 1-competitive when there is a reconfiguration overhead. We design an online algorithm that achieves a competitive ratio of 1−o(1) when the ratio between the minimum laxity of the packets and the number of ports tends to infinity. This is one of the rare cases where one can design an almost 1-competitive algorithm. One ingredient of our analysis, which may be interesting on its own right, is a perturbation theorem on EDF for the classical packets scheduling problem. Specifically, we show that a small perturbation in the release and deadline times cannot significantly degrade the optimal throughput. This implies that EDF is robust in the sense that its throughput is close to the optimum even when the deadlines are not precisely known.     

EXAM: a comprehensive environment for the analysis of access control policies

Policy integration and inter-operation is often a crucial requirement when parties with different access control policies need to participate in collaborative applications and coalitions. Such requirement is even more difficult to address for dynamic large-scale collaborations, in which the number of access control policies to analyze and compare can be quite large. An important step in policy integration and inter-operation is to analyze the similarity of policies. Policy similarity can sometimes also be a pre-condition for establishing a collaboration, in that a party may enter a collaboration with another party only if the policies enforced by the other party match or are very close to its own policies. Existing approaches to the problem of analyzing and comparing access control policies are very limited, in that they only deal with some special cases. By recognizing that a suitable approach to the policy analysis and comparison requires combining different approaches, we propose in this paper a comprehensive environment—EXAM. The environment supports various types of analysis query, which we categorize in the paper. A key component of such environment, on which we focus in the paper, is the policy analyzer able to perform several types of analysis. Specifically, our policy analyzer combines the advantages of existing MTBDD-based and SAT-solver-based techniques. Our experimental results, also reported in the paper, demonstrate the efficiency of our analyzer.     

An educational exercise examining the role of model attributes on the creation and alteration of CAD models

Computer-aided design (CAD) is a ubiquitous tool that today’s students will be expected to use proficiently for numerous engineering purposes. Taking full advantage of the features available in modern CAD programs requires that models are created in a manner that allows others to easily understand how they are organized and alter them in an efficient and robust manner. The results of a class-based exercise are presented to examine the role of model attributes on model creation, alteration, and student perception. Two popular CAD programs are used for the exercise: SolidWorks and Pro|Engineer. General results from both programs are reported. Fewer more complex features are found to be correlated with reduced modeling time. Simple features are shown to be positively correlated with the number of features retained without change. More complex features are found to be negatively correlated with the number of new features. Student perceptions of model quality and intuitiveness are positively correlated with the amount of feature reuse. Student survey data shows a preference for simpler features, the naming of features, and the use of reference geometry. The results do not allow for a generic approach regarding feature complexity to be prescribed. Overall, properly conveying design intent is shown to be positively correlated with design retention and negatively correlated with alteration time.     

Incentive mechanism for allocating total permitted pollution discharge capacity and evaluating the validity of free allocation

In this paper, the validity evaluation method of free allocation is studied under the background of allocating the total permitted pollution discharge capacity (TPPDC). First, the free allocation method’s localization and players’ strategic behaviors are analyzed. Second, an incentive mechanism for allocating TPPDC is proposed based on the uniform price auction of divisible goods, and an evaluation model to evaluate the validity for the free allocation of TPPDC is established, and the feasibility and reasonableness of this evaluation model are proved. Third, the evaluation criterion and the evaluation process are given. Finally, this evaluation model is applied to the environmental planning of Han River basin, and the validity evaluation result of free allocation is obtained by analyzing the statistical data of chemical oxygen demand (COD) in 14 counties and cities of Hubei Province, China. The results of our study will provide the government environmental management departments with theoretical basis and scientific methods to effectively implement the pollutant gross control system and design the related environmental policies.     

Ascorbic acid imprinted polymer-modified graphite electrode: A diagnostic sensor for hypovitaminosis C at ultra trace ascorbic acid level

A new kind of molecularly imprinted polymer-modified graphite electrode was fabricated by “grafting-to” approach, incorporating sol–gel technique, for the detection of acute deficiency in serum ascorbic acid level (SAAL), manifesting hypovitaminosis C. The modified electrode exhibited ascorbic acid (AA) oxidation at less positive potential (0.0 V) than the earlier reported methods, resulting in a limit of detection as low as 6.13 ng mL⁻¹ (RSD = 1.2%, S/N = 3). The diffusion coefficient (1.096 × 10⁻⁵ cm² s⁻¹), rate constant (7.308 s⁻¹), and Gibb's free energy change (−12.59 kJ mol⁻¹) due to analyte adsorption, were also calculated to explore the kinetics of AA oxidation. The proposed sensor was found to enhance sensitivity substantially so as to detect ultra trace level of AA in the presence of other biologically important compounds (dopamine, uric acid, etc.), without any cross interference and matrix complications from biological fluids and pharmaceutical samples.     

Application of ant colony, genetic algorithm and data mining-based techniques for scheduling

In this paper, we have proposed a novel use of data mining algorithms for the extraction of knowledge from a large set of flow shop schedules. The purposes of this work is to apply data mining methodologies to explore the patterns in data generated by an ant colony algorithm performing a scheduling operation and to develop a rule set scheduler which approximates the ant colony algorithm's scheduler. Ant colony optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems. The natural metaphor on which ant algorithms are based is that of ant colonies. Fascinated by the ability of the almost blind ants to establish the shortest route from their nests to the food source and back, researchers found out that these ants secrete a substance called ‘pheromone’ and use its trails as a medium for communicating information among each other. The ant algorithm is simple to implement and results of the case studies show its ability to provide speedy and accurate solutions. Further, we employed the genetic algorithm operators such as crossover and mutation to generate the new regions of solution. The data mining tool we have used is Decision Tree, which is produced by the See5 software after the instances are classified. The data mining is for mining the knowledge of job scheduling about the objective of minimization of makespan in a flow shop environment. Data mining systems typically uses conditional relationships represented by IF-THEN rules and allowing the production managers to easily take the decisions regarding the flow shop scheduling based on various objective functions and the constraints.