Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time arbitrary view synthesis method for ultra-HD auto-stereoscopic display

An arbitrary view synthesis method from 2D-Plus-Depth image for real-time auto-stereoscopic display is presented. Traditional methods use depth image based rendering (DIBR) technology, which is a process of synthesizing “virtual” views of a scene from still or moving images and associated per-pixel depth information. All the virtual view images are generated and then the ultimate stereo-image is synthesized. DIBR can greatly decrease the number of reference images and is flexible and efficient as the depth images are used. However it causes some problems such as the appearance of holes in the rendered image, and the occurrence of depth discontinuity on the surface of the object at virtual image plane. Here, reversed disparity shift pixel rendering is used to generate the stereo-image directly, and the target image won’t generate holes. To avoid duplication of calculation and also to be able to match with any specific three-dimensional display, a selecting table is designed to pick up appropriate virtual viewpoints for auto-stereoscopic display. According to the selecting table, only sub-pixels of the appropriate virtual viewpoints are calculated, so calculation amount is independent of the number of virtual viewpoints. In addition, 3D image warping technology is used to translate depth information to parallax between virtual viewpoints and parallax, and the viewer can adjust the zero-parallax-setting-plane (ZPS) and change parallax conveniently to suit his/her personal preferences. The proposed method is implemented with OPENGL and demonstrated on a laptop computer with a 2.3 GHz Intel Core i5 CPU and NVIDA GeForce GT540m GPU. We got a frame rate 30 frames per second with 4096×2340 video. High synthesis efficiency and good stereoscopic sense can be obtained. The presented method can meet the requirements of real-time ultra-HD super multi-view auto-stereoscopic display.
Novel method for determination of spot/line position in the array-based triangulation sensors

The method and circuit, which are presented in this note, offer the original solution for the extraction of a laser spot or trace from the intensity range images, using a simple hardware and software. Its advantages over existing profilers are numerous, and include the exclusion of frame- grabbers, flash A/D converters, strong processors, large memory requirements, mechanical parts and complex software algorithms.
Complexity in UAV cooperative control

This paper addresses complexity and coupling issues in cooperative decision and control of distributed autonomous unmanned aerial vehicle (UAV) teams. In particular, the recent results obtained by the inhouse research team are presented. Hierarchical decomposition is implemented where team vehicles are allocated to sub-teams using the set partition theory. Results are presented for single assignment and multiple assignments using the network flow and auction algorithms. Simulation results are presented for wide area search munitions where complexity and coupling are incrementally addressed in the decision system, yielding a radically improved team performance.
Reverse recovery processes in silicon power rectifiers

The present review gives an account of a number of investigations that have been recently carried out in the Semiconductor Laboratory Pretzfeld, Siemens AG. The switching processes in power rectifiers from the forward into the reverse state differ greatly from the corresponding process predicted by low-level theory. This result is caused not only by the fact that the conditions are different for high injection, but in addition, the sweeping out of the charge carriers takes place from two sides, owing to the nearly uniform concentration distribution in the forward state. Because of the unequal electron and hole mobilities, the impurity distribution on the side of the p contact is of much greater importance than at the n contact; if there is no p-n junction on this more important side, then the stored change can be swept out without much voltage buildup (example: rectifiers from uniformly doped p material). If, on the other hand, a p-n junction lies before the p contact (example: rectifiers from uniformly doped n material) then tbe reverse recovery current decays soon but slowly, and the switching process takes a longer time. This fact also contributes to the relatively long turn-off time of the thyristors.
Trainable question-answering systems

Research into automatic question answering systems has become increasingly popular as the internet age ripens. With current search engine technology and the explosion of web content, searching for a particular information need results in large amounts of information retrieved which must then be manually filtered and further searched. Question answering systems help to narrow down this search and in the optimum case presents just the desired answer. One alternative use of question answering systems is in the education field, to help satisfy the queries of students, relieving the work of teaching assistants and professors. This dissertation focuses on investigating statistical approaches to make a trainable question answering system. A question is first analyzed and a prediction is to be made as to what type of answer the user is expecting. For this, a maximum entropy model is derived using features of unigrams and bigrams and word position. Semantic classes of the question focus are shown to improve performance. Second, a fast search of the text database is performed and the top documents relevant to the query are retrieved. Finally, the answer tag prediction and the top documents are input to the answer selection stage. In this thesis, we investigate and report results on a trainable answer selection algorithm. The architecture presented here is similar to those investigated by other participants of the TREC-8 (Text Retrieval and Evaluation Conference) question and answering track. A new formal mathematical formulation of question answering is presented. The new formulation uses a training procedure which is independent of the type of questions. Results of the system are presented on the questions from the TREC conferences in 1999 and 2000.
Warning: The author of this document may have no mental states. Read at your own risk

" I may not have a brain gentlemen, but I have an idea " (B.O.B.). Two years ago my son had an accident and was taken to the intensive care unit at the Children's Hospital in San Diego, California. I was amazed at the high-tech symphony of human and machine activity that took care of my child and that is responsible for saving thousands of lives. Until recently robots have only been able to operate in highly controlled conditions, like medical and industrial settings. However, as Noel and Amanda Sharkey point out, recent advances in machine learning and machine perception are making possible a new generation of robots that may operate in unconstrained daily life environments. One potential application of such robots is early childhood education, the focus of this document. Educational robots may enrich our children's learning experiences in ways that we are only beginning to comprehend. The development of these robots requires for researchers to take a fresh look at the nature of human intelligence and is forcing them to pay close attention to the problems the brain solves when operating in daily life. It is also encouraging scientists and engineers to move beyond constrained laboratory conditions and to develop technology in close interaction with teachers, parents, and children to best serve their needs. This is the approach we took in the RUBI project, a scientific venture jointly funded by the University of California and Sony corporation during the years 2004 to 2008 (Tanaka et al., 2007). The goal of the project was to explore the possibilities of sociable robots in early childhood education. The challenges were great but not insurmountable and by the end of the project we managed to develop low cost robots that children, parents and teachers were really fond of. Most importantly the robots were able to operate fully autonomously for weeks at a time, teach 18–24 month old children foreign languages, and significantly improve the vocabulary development of their first language (Movellan et al.,
A new spectral analysis algorithm for SAR data processing of ScanSAR data and medium resolution data without interpolation

This paper describes a new approach for ScanSAR data image generation, which performs efficient data processing and multilook operation without the need of interpolation stages. This new technique is based on the spectral analysis method (SPECAN) combined with the well-known chirp Z-transform. In this paper, it is also shown that this new method is very efficient for obtaining near real-time images for browsing or on-board burst mode image generation overcoming classical problems of the standard SPECAN method.
Learning at the crossroads of biology and computation

Discusses various avenues for exploiting biological learning mechanisms within machine learning. Special attention is given to the following issues: (a) the reasons for the wide variety of biological learning mechanisms; (b) the relation between lifetime and genetic learning; (c) a description of the driving forces of genetic learning and their use in evolutionary computation. Various symbolic machine learning and reasoning techniques can be used to complement (genetic and/or neural) sub-symbolic learning. A first approach uses symbolic induction for explaining the behavior of (genetically evolved) neural nets. Next, a general framework for the use of (symbolic) domain knowledge during genetic learning is introduced. <<ETX>>
Towards an Open Repository of Teaching Resources

In this paper we describe our work to create a set of usability tools for CLARE, an EPrints installation storing Learning Objects. These tools include Web 2.0 style presentation and comments, and a concept map browser. Although the evaluation of our tools was broadly positive, through workshops with the language teaching community we discovered that a Learning Object repository is too heavyweight to be used as an everyday tool for sharing learning resources. In this paper we present the new requirements we elicited from the community, who wanted a lightweight, learning resource repository, with little metadata overhead, following the interface best-practices of popular online repository sites such as Flickr and YouTube.
Server-assisted prefetching for internet streaming media delivery

Delivering streaming media content over the Internet is a very challenging problem. Proxy servers has been introduced into the streaming media delivery systems over the Internet, and many mechanisms have been proposed based on this structure, such as proxy caching and prefetching. While the existing techniques can improve the performance of accesses to reused media objects, they are not effective in reducing the startup delay for first-time accesses. In this paper, we propose a more aggressive server-assisted prefetching mechanism to reduce the startup delay of first-time accesses. In this aggressive prefetching mechanism, proxy servers prefetch media objects before they are requested. To ensure the accuracy of this beforehand prefetching, we make use of server's knowledge about access patterns to locate the most popular media objects and provide such information to proxy servers as hint for prefetching. A proxy server makes decision based on the hint and its users' profile and prefetches suitable objects before they are accessed. Results of trace-driven simulations show that our proposed mechanism can effectively reduce the ratio of delayed requests by up to 38% with very marginal increase in traffic.
The line manager and systems-induced organization changes

A systematic method is presented for integrating organizational, technical, and business issues in the implementation of information technology at all stages in the life cycle. The approach is based on the assumption that line managers are the key to effective implementation. The discussion provides exemplars of positive and negative managerial behavior. A set of diagnostic frameworks and a prescriptive methodology are provided for assessing and managing the organizational impact of information technology. <<ETX>>
K-factor estimation in shadowed Ricean mobile communication channels

In this paper, a composite model for the received signal at the mobile unit is used to derive new moment-based estimators for the Ricean K-factor when shadowing is present. The results are then used to analytically evaluate the performance of the previously proposed moment-based estimators for K. It is proven that unlike existing moment-based estimators, the proposed estimators perform well in the presence of shadowing. Using simulations, it is also shown that the mean-squared error of the proposed estimators is significantly lower than that of the previously proposed estimators. Copyright © 2009 John Wiley & Sons, Ltd.
Comparative study on physicochemical and mechanical characterization of newnanocarbon-based hydroxyapatite nanocomposites

This study evaluated the effect of different additives such as nanocarbon compounds (0.5, 1.0, and 2.0 wt.%) with different morphologies and gelatin (Gel) (10 wt.%) on the mechanical properties of hydroxyapatite (Hap)- based nanocomposites (NCs). The NCs were prepared using the innovation process “SmartBox” based on the Internet of things (IoT), which provides process control and reproducibility, and they were characterized by X-ray diffraction, particle size distribution, transmission electron microscopy, Fourier transform infrared spectroscopy, and thermal analysis. The compressive strength tests demonstrated that the use of grapheme oxide (Hap_GO_2.0 - 133 N/mm2) , and/or Gel (Hap_Gel - 152 N/mm2) as additives to reinforce Hap (106 N/mm2) is more appropriate than the use of single functionalized multiwalled carbon nanotubes (Hap_fMWCNT_1.0 - 110 N/mm2) and fullerene (Hap_Ful_0.5 - 106 N/mm2) .
An Efficient Representation Method for ICLD with Robustness to Spectral Distortion

The inter‐channel level difference (ICLD) is a cue parameter to estimate spectral information in binaural cue coding that has been recently in the spotlight as a multichannel audio signal compression technique. Even though the ICLD is an essential parameter, it is generally distorted by quantization. In this paper, a new modified ICLD representation method to minimize the quantization distortion is proposed by adopting a flexible determination of the reference channel and the unidirectional quantization scheme. Our experimental result confirms that the proposed method improves the multichannel audio output quality even with the reduced bit‐rate.
The Evaluation of English Learning Level about Non-English Majors Based on Canonical Correlation Analysis

Th e English learning level about non-English majors was divided into three levels which are primary level (College entrance examination scores), secondary level (each semester final exam scores) and final level (CET-4 scores). The aim of this study is to examine the relationships between three levels by using canonical correlation analysis. The results indicated that the canonical correlation coefficients between three levels are 0.685, 0.6523 and 0.7566, which illustrated that canonical correlation relation between three levels was remarkable. In addition, the results indicated that the indicators of the level have larger load in the indicator of other levels. Students were also offered some targeted advices in proving English learning level.
Role of formant frequencies and bandwidths in speaker perception

This paper considers the relation between the vocal tract characteristics under the personality of speech. A pitch synchronous analysis-synthesis system was constructed in which the formant frequencies and the bandwidths can be modified independently. The speech was synthesized by controlling these parameters in natural speech, and an experiment was made on the discrimination of personalities. As a result, it is seen that the personality is strongly sensitive to the formant frequency shift, especially to the shift of the lower three formants, and it is lost by the uniform shift of 5 percent. On the other hand, the personality is well preserved for the change of formant bandwidth, and is sensitive to the bandwidth change in the fourth- and higher-order for-mants. In the case of uniform change of the bandwidth, deformation of wider than 5 times or narrower than one-fifth times completely eliminates the personality.
A comparative robustness evaluation of feedforward neurofilters

A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.
PROFIT ESTIMATION FOR A PRODUCT UNDER WARRANTY: AN EVALUATION BASED ON CUSTOMER'S EXPECTATION AND SATISFACTION

Performance of a product not as expected by the customer brings warranty expenditure into the picture. In other words, the deviation of the product performance (PP) from the customer expectation (CE) is the reason for customer complaints and warranty expenses. When this conflicting scenario occurs in market, warranty comes into existence and fulfilling warranty claims of customers adds to product's overall cost. In this paper, based on the difference between PP and CE about the product we estimate profit for the firm. Furthermore, factors like fixed cost, production cost and inventory cost have also been considered in framing the optimization problem. In the proposed model, a two-dimensional innovation diffusion model (TD-IDM) which combines the adoption time of technological diffusion and price of the product has been used. Classical Cobb–Douglas function that takes into account the technological adoptions and other dimensions explicitly has been used to structure the production function. The proposed model has been validated on real life data set.
Recent advances in control of time delay systems-a tutorial review

In this survey, we focused on recent advances on robust control for time delay systems and an application of delay. Finite spectrum assignment approach, Bezout factorization approach and H/sup /spl infin// control to robust control were presented. A deadbeat control of continuous-time systems is shown as an interesting positive usage of time-delay.
Object Recognition with Adaptive Decision Trees

It is conjectured that humans learn to recognize objects by incrementally modifying and extending an internal representation based on the characteristics which distinguish objects from the rest of the environment. As new objects are encountered, it is often required to recall similar yet distinct objects and determine what differentiates the new objects from the old. Sometimes all that is required is to refine the allowable range for a particular feature, i.e., use a higher level of precision. Other times a previously useful feature must be discarded for a more powerful one in order to perform efficient recognition. This paper describes a system which has been developed based on this conjecture. Initially, a decision tree is created for recognizing a set of training objects using an automatically selected subset of extractable features. Factors involved in the creation include the cost of extraction and comparison of features, their discriminating strength within the domain, and the stability or separability of classes of objects using the features. The system then allows incremental, local modification of the tree to accommodate new objects or instances of old objects which were incorrectly identified. Various strategies for tree modification have been implemented, some of which guarantee the correct recognition of objects previously recognized and others which require some degree of retraining to maintain perfect recollection. Strategy selection is based on the technique which minimizes a metric based on the increased cost and complexity of the tree and the potential decrease in the stability of recognition.
A high sensitivity force sensor for microassembly: design and experiments

This paper aims at advancing micromanipulation technology with in-situ PVDF piezoelectric force sensing during microassembly and packaging process. To allow close monitoring of magnitude and direction of forces (adhesion, surface tension, friction, and assembly force) acting on micro devices during manipulation, the polyvinylidene fluoride (PVDF) is used to fabricate highly sensitive 1-D and 2-D sensors for assembly of micro devices. By using an electronic circuit designed with the effective data processing techniques, the contact/impact force signal can be obtained desirably and then is fed back for improving the reliability of assembly. The calibration of the sensor has been conducted on a high precision optical microscope system with the optimal image processing methods. Preliminary calibration results verify the effectiveness of the sensor model with high sensitivity as well as a resolution in the range of sub-/spl mu/N. Furthermore, experiments demonstrate the performance of the force sensing system. Ultimately the technology will provide a critical and major step towards the development of automated manufacturing processes for batch assembly of micro devices.
An Appraisal Of Artificial Intelligence Techniques For Industrial Vision Systems

The role of Artificial Intelligence (AI) in industrial vision systems is examined. It is concluded that there are several, quite distinct areas where AI concepts and techniques are likely to be useful. The first is that of designing and planning industrial vision systems. The most obvious application is probably that of analysing complex scenes, about which little or nothing is known in advance. However, the author argues that in a well designed industrial plant there is very little disorder. For example, the orientation of piece parts would not be lost by tossing them into a bin. The cost of re-orientating them can be quite expensive. The well known "bin picking" problem is thus seen as one for which solutions should be sought but instead avoided. The third area where AI techniques might be used is in the task of inspecting either complex objects / assemblies, or those which are made in small quantities. The paper concludes with a discussion about the requirement for a convenient language for expressing both image processing and AI algorithms. The structure of such a language is described.
A 1.8 GHz CMOS fractional-N frequency synthesizer with randomized multi-phase VCO

A synthesizer in 0.6 /spl mu/m CMOS with an on-chip multiphase VCO exhibits no spurs resulting from interpolated phase errors. The proposed architecture randomizes phase errors of the multi-phase VCO to eliminate spurious tones generated by phase mismatch. Phase noise measured at 1.715 GHz is lower than -80 dBc within 20 kHz loop bandwidth and -118 dBc at 1 MHz offset with fractional spur below -70 dBc. The chip consumes 140 mW at 3.3 V and occupies 3.7 mm/spl times/4.6 mm.