Miracle-dz/UniFAR-FTUs huggingface dataset:
PCA facial expression recognition

This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. The comparative study of Facial Expression Recognition (FER) techniques namely Principal Component’s analysis (PCA) and PCA with Gabor filters (GF) is done. The objective of this research is to show that PCA with Gabor filters is superior to the first technique in terms of recognition rate. To test and evaluates their performance, experiments are performed using real database by both techniques. The universally accepted five principal emotions to be recognized are: Happy, Sad, Disgust and Angry along with Neutral. The recognition rates are obtained on all the facial expressions.
Text-independent talker identification with neural networks

The authors introduce a novel method for partitioning a large classification problem using N*(N-1)/2 binary pair classifiers. The binary pair classifier has been applied to a speaker identification problem using neural networks for the binary classifiers. The binary partitioned approach was used to develop an identification system for the 47 male speakers belonging to the Northern dialect region of the TIMIT database. The system performs with 100% accuracy in a text-independent mode when trained with about 9 to 14 s of speech and tested with 8 s of speech. The partitioned approach performs comparably, or even better, than a single large neural network. For large values of N (>10), the partitioned approach requires only a fraction of the training time required for a single large network. For N=47, the training time for the partitioned network would be about two orders of magnitude less than for the single large network. <<ETX>>
CDHMM parameters selection for speaker-independent phone recognition in continuous speech system

Pattern recognition has long been a topic of fundamental importance in a wide range of science and technology. Over the years there have been a range of several tasks developed for speech recognition. While in recent years speech recognizer evaluation has focused on LVCSR research, we believe that evaluating recognition at the phone level is important since the words are always represented by the concatenation of phones units. These phones are acoustically modeled by the predominant static model in automatic speech recognition remains the Hidden Markov Model ‘HMM’. In this paper, we investigate the behavior of speaker-independent phone recognition in continuous speech based on the technique of HMM. This study focus on the selection of an optimal model topology in order to achieve a robust phone recognition system which accomplishes the tradeoff between model size and data training. To evaluate and compare the performance of our conceived system to other previous works, we choose the standard TIMIT Database and the platform HTK. We obtain a phone recognition correct rate 69.33 percent and accuracy rate of 63.05 percent which are comparable with others works.
Less conservative criteria for fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer

This paper studies the problem of fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer. Based on the proposed fast adaptive fault estimation (FAFE) algorithm using only a measured output, a delay‐dependent criteria is first established to reduce the conservatism of the design procedure, and the FAFE algorithm can enhance the performance of fault estimation. On the basis of fault estimation, the observer‐based fault‐tolerant tracking control is then designed to guarantee tracking performance of the closed‐loop systems. Furthermore, comprehensive analysis is presented to discuss the calculation steps using linear matrix inequality technique. Finally, simulation results of a stirred tank reactor model are presented to illustrate the efficiency of the proposed techniques. Copyright © 2009 John Wiley & Sons, Ltd.
Systematic treatment of order-recursive least-squares algorithms

In this paper we show that the order recursive least squares (LS) algorithms can be systematically studied as follows: (1) Determine various estimator structures (connection of basic building cells) based on the known properties of the input data vector and required output, and (2) Investigate possible realizations of time-updating and their properties implemented in the elementary cells. In view of this approach, we show that using a structure from (1) in combination with a time-update realization from (2) almost always forms a valid order-recursive LS (ORLS) algorithm. All known ORLS algorithms can be derived under a unified framework by using this approach. The properties of ORLS algorithms, such as computational complexity and sensitivity to the round-off error, can also be investigated in a systematic manner. This method not only simplifies the investigation of existing algorithms, but it also is powerful enough for creating new ORLS algorithms. These points will become clearer during the course of the development of this paper.
Multi-channel time-frequency data fusion

This paper proposes an efficient mechanism for the fusion of two noisy speech signals obtained by an array of two microphones using single-tap time-frequency filters and by taking into account the correct time delay of arrival (TDOA) of the speech source. Speech signals obtained by the microphones are transformed into a set of two complex time-frequency (TF) images. By knowing the correct TDOA, and therefore the associated phase difference between the signals at each frequency, it is possible to non-linearly filter both the real and the imaginary parts of the TF images. This will consist of a TF reward-punish filter that adjusts the amplitude of the TF blocks based upon the variation of their phase-difference with the ideal phase-difference defined by the TDOA. Simulation results show that the proposed technique can achieve a Signal-to-Noise Ratio (SNR) improvement of 15 dB when there, is strong Gaussian noise present (-20 dB initial SNR). When the original SNR is OdB, the simulated improvement is approximately 8 dB. It is also shown that although the proposed technique is a more general case of the adaptive beamformer (where the adaptive beamformer has a specific reward-punish characteristic), other reward-punish characteristics that are proposed in this paper can often surpass the performance of the ideal adaptive beamformer.
A discrete-time analog signal processor for disk read channels

A signal processor that incorporates equalization, clock recovery, AGC (automatic gain control), and peak detection for waveforms in the disk read channel and operates up to a 40-MHz clock rate is described. The 2- mu m CMOS IC uses precision analog MOS signal processing implemented with scaled-down unit cells and dissipates 500 mW from a 5-V power supply. The IC layout is hand-crafted. The 6.8-mm*4.6-mm die is fabricated in a 2- mu m, double-poly, double-metal technology. Measurements on one half-delay cell show a transfer efficiency of 0.994 and 10-b linearity across full-scale. <<ETX>>
On improving the performance of shared buffered banyan networks

The paper investigates three methods that will improve the performance of shared buffered banyan networks: cut through routing, biased conflict resolution, and speedup. The authors present analytical and simulation results for a shared buffered banyan multistage interconnection network (MIN) consisting of 2/spl times/2 (2 input and 2 output) switch elements (SEs) subjected to both uniform and unbalanced traffic patterns, with and without speedup. They show that when no speedup is used, the adoption of cut through routing in a shared buffered banyan MIN significantly improves the performance of the MIN. However when speedup at high loads is employed, the performance of the MIN is largely dependent on the size of the shared buffer in each SE and the output buffer size. They also propose two conflict resolution algorithms to improve MIN performance.
On-chip normal flow computation with aperture problem compensation circuitry

Extracting relevant visual information about the operating environment of a roving robot at the focal plane is a challenging problem. We present two image processing architectures for motion computation at the focal plane. The first imaging architecture, composed of 250 x 250 active pixel sensors, has spatiotemporal difference computation capabilities at the focal plane. This spatiotemporal difference imager, fabricated in a 0. 35μ process, contains in-pixel storage elements for previous and current frames and difference computational units outside the imaging array. A novel scan out technique allows for parallel computation of spatial and temporal 1-D derivatives on the read out. The final motion estimation based on the image brightness constancy equation, which is approximated as the ratio of the temporal and spatial derivates, is computed off chip, but it can be easily implemented on-chip. This approach can only determine the motion component normal to the spatial gradient. In order to address this ill-posed problem, known as the aperture problem, we propose a second imaging architecture, which is an extension of the first imaging architecture. The latter imaging architecture contains in-pixel memory for storing partial computational results. Hence, the motion vectors are stored back into the pixel memories after an initial scan; iterative algorithms can be applied to the stored computational results to solve the aperture problem. Experimental data from both imaging architectures are presented to validate the accuracy of the magnitude and angle of the computed target velocities.
History educators and the challenge of immersive pasts: a critical review of virtual reality ‘tools’ and history pedagogy

This paper will undertake a critical review of the impact of virtual reality tools on the teaching of history. Virtual reality is useful in several different ways. History educators, elementary and secondary school teachers and professors, can all profit from the digital environment. Challenges arise quickly however. Virtual reality technologies show great pedagogical promise in the presentation of research. It is also asserted that these technologies provide real‐world immersion in the ‘historical past’ in a way that was previously not possible. Can these systems truly take the place of classrooms, elementary and secondary, and the research projects of graduate studies? Ultimately, technological optimists argue that these technologies create an ‘alternate reality’. Can history educators agree to such an ‘alternate reality’? The principle conclusions drawn in this paper include a need for further development of virtual simulations, both in terms of their realism and the immediacy of the classroom experience. Further practical experimentation by history educators in the research environment is also key.
Robust run-to-run control for semiconductor manufacturing: an internal model control approach

This paper presents the design of run to run (RtR) controllers using the internal model control (IMC) structure. In RtR control the input recipe for a run is determined using the in-situ and ex-situ measurements of past runs. RtR controllers utilizing linear response surface models are considered. The RtR controllers are designed to be robust with respect to modeling error and incorporate measurement delays. The RtR IMC filter design is modified to compensate for process drifts, and to account for the inherent unit measurement delay that exists for RtR control. A detailed robustness analysis is presented to obtain good stability and performance. These conditions are used to a priori predict achievable process performance. Simulations show that the developed RtR controllers are able to control the process even in the presence of sudden disturbances, measurement delays and reactor aging. Simulations also show that they perform better than exponentially weighted moving average controllers.
Sidelobe reduction in sparse linear arrays by genetic algorithms

A numerical procedure based on a genetic algorithm is proposed in order to synthesize a linear, sparse, and aperiodic array to be used in a beamforming processor. The method is aimed to minimize the sidelobe peak of the beam pattern acting on the elements' positions and weights. Obtained results also confirm the effectiveness of the approach in comparison with other techniques in the related literature. © 2002 John Wiley & Sons, Inc. Microwave Opt Technol Lett 32: 194–196, 2002.
A Study on Attributional and Relational Similarity between Word Pairs on the Web

報告番号: 甲25374 ; 学位授与年月日: 2009-09-28 ; 学位の種別: 課程博士 ; 学位の種類: 博士(情報理工学) ; 学位記番号: 博情第256号 ; 研究科・専攻: 情報理工学系研究科電子情報学専攻
An Analysis of Volunteer Age and Level of Education on Performance in ‘Readability’ Testing for Patient Information Leaflets (PILs)

The success and safety of a medicine depends on the clarity and completeness of information given with it. Since July 2005 it has been a requirement in the EU that PILs ‘shall reflect the results of consultations with target patient groups to ensure that it is legible, clear and easy to use’. The ‘User Test’ or Readability Test has been the method of choice for most pharmaceutical companies to fulfil this requirement.
The chronology of geographic information system image processing: a case study for land changes at Nusajaya, Iskandar Malaysia

In the last few years, land demands in Iskandar Malaysia become important issues for stakeholders and town planners. Our study case area is at Nusajaya, Iskandar Malaysia. The motivation and the goal of this paper is to investigate four mathematical modelling in image processing integrate with GIS such as CA-GIS integration, ANN-GIS integration, neural network based cellular automata-GIS and GAC-AOS model. Geographic Information Systems (GISs) is the combination of cartography, statistical analysis and computer science technology. The general GIS have its limitation in modelling changes in the landscape overtime. Integration GIS with CA and ANN, will overcome the drawbacks of GIS. Geodesic Active Contour (GAC) model are used to detect the edges of Nusajaya images. Thus some classical numerical methods (Gauss-Seidel and Jacobi method) are used to solve the system linear of equations and the experimental results demonstrate that the Gauss-Seidel (GS) method gives the best performance compared to Jacobi (JB) method. © 2014 American Scientific Publishers All rights reserved.
Critical Issues for Knowledge Management Implementation at a National Level

Purpose: To date, critical success factors for designing and implementing knowledge management system at a national level for the countries have not been systematically investigated. Existing studies have derived their critical success factors from companies’ perspectives and have not considered the needs of a larger scale such as a country and at a national level. This paper is aimed to bridge this gap.Design/Methodology/Approach: A qualitative case study technique has been used in this paper for data collection to gain insights into the topic being investigated. For that, “grounded theory” research approach has been selected by which the collected data from real case studies (European countries) are categorized and analyzed through specific stages. The extracted concepts can demonstrate critical success factors of knowledge management master plan at a national level.Findings: The overall results from the real case studies were positive, thus reflecting the appropriateness of the proposed critical success factors. Also 20 concepts and one semantic network are the other findings of this research that clarify how to design and implement a knowledge management system at a national level. The semantic network shows the most important factors (concepts), their effects on each other, and their relations.Practical Implications: The set of critical success factors can act as a list of items for countries to address when adopting knowledge management. This helps to ensure that the essential issues and factors are covered during design and implementation phase. For academics, it provides a common language for them to discuss and study the factors crucial for the success of knowledge management master plan at a national level.Originality/Value: This study is probably the first to provide an integrative perspective of critical success factors for implementing KM level in the countries. It gives valuable information and guidelines which hopefully will help the governments to accomplish knowledge management through their countries.
Further GPU implementation of prediction-based lower triangular transform using a zero-order entropy coder for ultraspectral sounder data compression

The ultraspectral sounder data consists of two dimensional pixels, each containing thousands of channels. In retrieval of geophysical parameters, the sounder data is sensitive to noises. Therefore lossless compression is highly desired for storing and transmitting the huge volume data. The prediction-based lower triangular transform (PLT) features the same de-correlation and coding gain properties as the Karhunen-Loeve transform (KLT), but with a lower design and implementational cost. In previous work, we have shown that PLT has the perfect reconstruction property which allows its direct use for lossless compression of sounder data. However PLT is time-consuming in doing compression. To speed up the PLT encoding scheme, we have recently exploited the parallel compute power of modern graphics processing unit (GPU) and implemented several important transform stages to compute the transform coefficients on GPU. In this work, we further incorporated a GPU-based zero-order entropy coder for the last stage of compression. The experimental result shows that our full implementation of the PLT encoding scheme on GPU shows a speedup of 88x compared to its original full implementation on CPU.
ERPs and task effects in the auditory processing of gender agreement andsemantics in French

We investigated task effects on violation ERP responses to Noun-Adjective gender mismatches and lexical/conceptual semantic mismatches in a combined auditory/visual paradigm in French. Participants listened to sentences while viewing pictures of objects. This paradigm was designed to investigate language processing in special populations (e.g., children) who may not be able to read or to provide stable behavioural judgment data. Our main goal was to determine how ERP responses to our target violations might differ depending on whether participants performed a judgment task (Task) versus listening for comprehension (No-Task). Characterizing the influence of the presence versus absence of judgment tasks on violation ERP responses allows us to meaningfully interpret data obtained using this paradigm without a behavioural task and relate them to judgment-based paradigms in the ERP literature. We replicated previously observed ERP patterns for semantic and gender mismatches, and found that the task especially affected the later P600 component.
Data quality system using reference dictionaries and edit distance algorithms

The real art of management it is important to make smart decisions, what in most of the cases is not a trivial task. Those decisions may lead to determination of production level, funds allocation for investments etc. Most of the parameters in decision-making process such as: interest rate, goods value or exchange rate may change. It is well know that these parameters in the decision-making are based on the data contained in datamarts or data warehouse. However, if the information derived from the processed data sets is the basis for the most important management decisions, it is required that the data is accurate, complete and current. In order to achieve high quality data and to gain from them measurable business benefits, data quality system should be used. The article describes the approach to the problem, shows the algorithms in details and their usage. Finally the test results are provide. Test results show the best algorithms (in terms of quality and quantity) for different parameters and data distribution.
Extracting road centrelines from high-resolution satellite images using active window line segment matching and improved SSDA

This paper presents a new semi-automatic approach to extracting main road centrelines from high-resolution satellite images. The approach is based on active window line segment matching and an improved sequential similarity detection algorithm (SSDA). First, a user-specified point on the road centreline is selected as a reference central point to define a template window, and a thresholding operation is performed within the window. Then a best matched target window along the road is searched to determine the next central point in the road. To avoid the influence of noise, only the line segment of ‘interest’ in the window is matched. An improved SSDA searching strategy is proposed to increase the matching speed. When the best matched target window is found, its centre is used as the next central point in the road, and a new template window is generated. By repeating the matching process, a series of central points can be obtained automatically and the corresponding final road centreline from them is extracted. Our approach also allows some kinds of user interventions in case automatic tracking fails. Experimental results confirm that the proposed approach is capable of rapidly and accurately extracting main road centrelines and has good robustness against noise.
The artificially intelligent computer performer: The second generation

Abstract While much research has been done on modeling human performance on a computer and several systems have been successful, few researchers have addressed the task of equipping the “artificial performer” with as much information about the score as a human performer. Highly sophisticated tracking algorithms have been developed but there remains much to be done on the problems of “musicalization” and “ensemble interaction” (group dynamics). The Artificially Intelligent Computer Performer (AICP) addresses these problems and presents a user Journal of New Music Research that is at once intuitive and pedagogical. It uses a commercially available notation and sequencing program for score input. Heuristics are invoked which overlay tracking algorithms and transform the AICP from its tradional role as an accompanist into a more intelligent decision maker. This paper accompanies a demonstration of the AICP and explains the operation of the program, as well as some of our solutions to the problems described ab.
Image Quality Assessment Based on Region of Interest

In this paper a new No-Reference (NR) image quality assessment (IQA) method based on the point wise statistics of local normalized luminance signals using region of interest (ROI) processing is proposed. This algorithm firstly extracts the ROI which is relative to human subjectivity by using the image gradient and phase congruency, and then extracts the image quality feature in spatial domain. Particularly, most of the present IQA methods mainly focus on predicting the image quality with respect to human perception, yet, in some other image domains, the final receiver of a digital image may not a human. Thus, we propose a method which can assess the image quality relative to edge detection algorithm. In addition, experimental results on LIVE database are provided to justify the superior compared to the significant image quality metrics.
Traffic management in a band limited communication network: an optimal control approach

This paper focuses on the scheduling and congestion control problems for a band limited communication network, taking into account the QoS requirements of the various connections. The problem is tackled and solved using optimal control methodologies. The optimal solution is given a closed form representation and is characterized by the classical closed loop structure. Applications against simulated realistic data show the improvements achievable by the proposed approach.