A low cost, non-individualized surround sound system based upon head related transfer functions: an ergonomics study and prototype development

This paper reports on the types and magnitudes of localization errors of simulated binaural direction cues generated using non-individualized, head-related transfer functions (HRTFs) with different levels of complexity. Four levels of complexity, as represented by the number of non-zero coefficients of the associated HRTF filters (128, 64, 32, 18 non-zero coefficients), were studied. Experiment 1 collected 1728 data runs that were exhaustive combinations of the four levels of complexity, nine simulated directions of sound (no direction (i.e., diotical-mono), 0 degrees , 45 degrees , 90 degrees , 135 degrees , 180 degrees , 225 degrees , 270 degrees , and 315 degrees azimuth angles at 0 degrees elevation), two repetitions, and 24 participants). Binaural cues generated from HRTFs of reduced complexity (from 128 to 18 non-zero coefficients) produced significantly higher localization errors for the directions of 45 degrees , 135 degrees , 225 degrees , and 315 degrees azimuth angles (p<0.01). From the directions of 0 degrees , 90 degrees , and 270 degrees azimuth angles, the cues produced by HRTFs with reduced complexity did not affect the localization error (p>0.2). Surprisingly, cues produced by HRTFs of 128 non-zero coefficients did not have the lowest number of errors. From 45 degrees , 135 degrees , 225 degrees , and 315 degrees , the lowest numbers of errors were obtained from cues produced by HRTFs of 64, 32, 32, and 64 non-zero coefficients, respectively. Based on these findings, a prototype virtual headphone-based surround-sound (VHSS) system was developed. A double-blind usability experiment with 32 participants indicated that the prototype VHSS system received significantly better surround-sound ratings than did a Dolby stereo system (p<0.02). This paper reports results from an original ergonomics study and the application of these results to the design of a consumer product.     

Genetic Parallel Programming: design and implementation

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.     

Segmentation of telecom customers based on customer value by decision tree model

The more the telecom services marketing paradigm evolves, the more important it becomes to retain high value customers. Traditional customer segmentation methods based on experience or ARPU (Average Revenue per User) consider neither customers’ future revenue nor the cost of servicing customers of different types. Therefore, it is very difficult to effectively identify high-value customers. In this paper, we propose a novel customer segmentation method based on customer lifecycle, which includes five decision models, i.e. current value, historic value, prediction of long-term value, credit and loyalty. Due to the difficulty of quantitative computation of long-term value, credit and loyalty, a decision tree method is used to extract important parameters related to long-term value, credit and loyalty. Then a judgments matrix formulated on the basis of characteristics of data and the experience of business experts is presented. Finally a simple and practical customer value evaluation system is built. This model is applied to telecom operators in a province in China and good accuracy is achieved.     

Synthesis, characterization, and properties of poly(ethylene terephthalate)/poly(1,4-butylene succinate) block copolymers

Reactive blending at 290 °C of a series of mixtures of poly(ethylene terephthalate) (PET) and poly(1,4-butylene succinate) (PBS) led to the formation of block PET/PBS copolyesters. The block lengths of the resulting copolymers decreased with the severity of the treatment. Copolyesters with PET/PBS molar compositions of 90/10, 80/20, 70/30, and 50/50 were prepared by this method and their composition and microstructure were characterized by ¹H and ¹³C NMR, respectively. The T_g, T_m, and crystallinity of the copolymers decreased as the content in PBS and the degree of randomness increased. The elastic modulus and tensile strength of the copolymers decreased with the content of PBS, whereas, on the contrary, the elongation at break increased. The PET/PBS copolymers exhibited a pronounced hydrolytic degradability, which increased with the content in 1,4-butylene succinic units. Hydrolysis mainly occurred on the aliphatic ester groups.     

Detecting improvement using Shewhart attribute control charts when the lower control limit is zero

In this paper, we present a method to monitor count data so as to be able to detect improvement when the counts are low enough to cause the lower limit to be zero. The method, which is proposed as an add-on to the conventional Shewhart control chart, consists in counting the number of samples in which zero defectives or zero defects per unit occur and signaling an increase in quality if k-in-a-row or 2-in-t samples have zero counts of defectives or zero defects per unit. This method enjoys some similarities to the very popular Shewhart control chart in that it is easy to design, understand and use. It is flexible, robust, and, like the Shewhart chart, yields detection frequencies that are optimal for very large shifts and good for other shifts. Some comparisons with traditional CUSUM charts are provided. Figures enabling Shewhart control chart users to easily design low-side add-on control charts are given for c and np charts.     

Prediction of the obstacle effect on film-boiling heat transfer

A correlation has been developed to account for the effect of obstacles (simulating the spacing devices in bundles) on heat transfer in dispersed-flow film boiling. The correlation is expressed as a modification factor to the reference geometry without any obstacles. The basic form of the correlation is an exponential decay function that resembles the diminishing effect on turbulence enhancement. The coefficients and constants in the correlation have been optimized with heat-transfer data of low-pressure single-phase (air) flow and high-pressure steam-water flow at film-boiling conditions.An experiment has been set up to obtain validation data with a heated tube of 4.1 mm inside diameter. HFC-134a was used as the working fluid. Three types of obstacles with the same blockage-area ratio of 37.8% were tested. The results showed that the obstacles exhibited a strong enhancement effect on the film-boiling heat-transfer coefficient at locations downstream of the obstacles. A comparison between predictions of the correlation for the spacing-device effect and experimental data showed an underprediction of the heat-transfer rate at locations downstream of the obstacle. The underprediction is due mainly to the rewetting of the heated surface at the location of an obstacle, beyond which the developing film-boiling effect becomes dominant. The agreement between prediction and data is significantly improved after accounting for the critical heat flux (CHF) enhancement and developing film-boiling effects in the calculations.     

HIGH‐DIMENSIONAL LEARNING FRAMEWORK FOR ADAPTIVE DOCUMENT FILTERING*

We investigate the unique requirements of the adaptive textual document filtering problem and propose a new high‐dimensional on‐line learning framework, known as the REPGER (relevant feature pool with good training example retrieval rule) algorithm to tackle this problem. Our algorithm possesses three characteristics. First, it maintains a pool of selective features with potentially high predictive power to predict document relevance. Second, besides retrieving documents according to their predicted relevance, it also retrieves incoming documents that are considered good training examples. Third, it can dynamically adjust the dissemination threshold throughout the filtering process so as to maintain a good filtering performance in a fully interactive environment. We have conducted experiments on three document corpora, namely, Associated Press, Foreign Broadcast Information Service, and Wall Street Journal to compare the performance of our REPGER algorithm with two existing on‐line learning algorithms. The results demonstrate that our REPGER algorithm gives better performance most of the time. Comparison with the TREC (Text Retrieval Conference) adaptive text filtering track participants was also made. The result shows that our REPGER algorithm is comparable to them.     

An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem

As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novel learning rule. It is called the integrated SOM (ISOM) since its learning rule integrates the three learning mechanisms in the SOM literature. Within a single learning step, the excited neuron is first dragged toward the input city, then pushed to the convex hull of the TSP, and finally drawn toward the middle point of its two neighboring neurons. A genetic algorithm is successfully specified to determine the elaborate coordination among the three learning mechanisms as well as the suitable parameter setting. The evolved ISOM (eISOM) is examined on three sets of TSP to demonstrate its power and efficiency. The computation complexity of the eISOM is quadratic, which is comparable to other SOM-like neural networks. Moreover, the eISOM can generate more accurate solutions than several typical approaches for TSP including the SOM developed by Budinich, the expanding SOM, the convex elastic net, and the FLEXMAP algorithm. Though its solution accuracy is not yet comparable to some sophisticated heuristics, the eISOM is one of the most accurate neural networks for the TSP.     

Design of an interactive video-on-demand system

We design an interactive video-on-demand (VOD) system using both the client-server paradigm and broadcast delivery paradigm. Between the VOD warehouse and customers, we adopt a client-server paradigm to provide an interactive service. Within the VOD warehouse, we adopt a broadcast delivery paradigm to support many concurrent customers. In particular, we exploit the enormous bandwidth of optical fibers for broadcast delivery, so that the system can provide many video programs and maintain a small access delay. In addition, we design and adopt an interleaved broadcast delivery scheme, so that every video stream only requires a small buffer size for temporary storage. A simple proxy is allocated to each ongoing customer, and it retrieves video from optical channels and delivers video to the customer through an information network. The proposed VOD system is suitable for large scale applications with many customers, and has several desirable features: 1) it can be scaled up to serve more concurrent customers and provide more video programs, 2) it provides interactive operations, 3) it only requires point-to-point communication between the VOD warehouse and the customer and involves no network control, 4) it has a small access delay, and 5) it requires a small buffer size for each video stream.