Miracle-dz/UniFAR-FTUs huggingface dataset:
An embedded wavelet packet image coding algorithm

In this paper, we presented a novel wavelet packet image coding approach which provides the functionality of fine granular bitstream scalability. The proposed progressive wavelet packet image coding scheme consists of three parts, wavelet packet decomposition, a quadtree sorting procedure for classifying wavelet coefficients and universal trellis-coded quantization for quantizing the sorted coefficients. The image coding results, calculated in PSNR and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results, due to the flexible representation ability of wavelet packet, the effective quadtree classifier and the improved granular fidelity of the UTCQ over scalar quantization.
An efficient iris recognition system

Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, and is most promising for high security environments. A new iris recognition algorithm is proposed in this paper, which adopts Independent Component Analysis (ICA) to extract iris texture feature and a competitive learning mechanism to recognize iris patterns. Experimental results show that the algorithm is efficient and adaptive to the environment, e.g. it works well even for blurred iris images, variable illumination, and interference of eyelids and eyelashes.
Dynamic bayesian forecasting models of football match outcomes

Dynamic Generalized Linear Models (DGLMs) are essentially generalised linear models with parameters that are stochastic. They are Bayesian in flavour and are particularly suited to forecasting applications. This paper outlines a practical implementation of a Poisson DGLM model that can easily be deployed using the freely available software WinBUGS. Using match results data from the Scottish Premier League (SPL) between 2003/2004 to 2005/2006, the DGLM approach is shown to provide more improved predictive probabilities of future match outcomes, compared to the non-dynamic form of the model.
A webGL talking head for mobile devices

Luciaweb is a 3D Italian talking avatar based on the new WebGL technology. WebGL is the standard programming library to develop 3D computer graphics inside the web browsers. In the last year we developed a facial animation system based on this library to interact with the user in a bimodal way. The overall system is a client-server application using the http protocol: we have a client (a browser or an app) and a web server. No software download and no plugin are required. All the software reside on the server and the visualization player is delivered inside the html pages that the client ask at the beginning of the connection. On the server side a software called AudioVideo Engine generates the phonemes and visemes information needed for the animation. The demo called Emotional Parrot shows the ability to reproduce the same input in different emotional states. This is the first WebGL software running on iOS device ever.
Novel decision-directed channel estimation method for TDS-OFDM system

Time-domain synchronous orthogonal frequency division multiplexing system (TDS-OFDM) employs known pseudo-noise (PN) sequences as guard interval padding between adjacent OFDM symbols. Accurate estimation of channel impulse response (CIR) is difficult but very important to recover transmitted OFDM symbols by subtracting padded PN sequences. Conventional channel estimation methods only use PN sequences as the training sequences to obtain CIR. Actually, decision-directed channel estimation (DDCE) method which takes advantage of the fact that M-QAM modulated subcarriers in OFDM symbol also contain much valuable hidden-information due to regular constellation mapping and can be used to improve the accuracy of channel estimation. In this paper, the accuracy of channel estimation based on both PN sequence and OFDM symbol is investigated. Moreover, a novel DDCE method based on an accurate initial CIR obtained from two consecutive training sequence and partial decision results of OFDM subcarriers for TDS-OFDM system is proposed. Simulation results show that the proposed algorithm works well over the slow-varying frequency-selective fading channel.
The augmented bush walk: adaptation in crossmedia ecologies

Contemplative interaction appears to be a misnomer; the term 'interaction' implies active engagement rather than quiet reflection. However, we are often engaged on multiple levels simultaneously, particularly inside complex systems. The bushwalk is an active engagement with the environment - a naturally occurring complex system - that occupies the body while the mind is adrift. Similarly, digital systems, such as games - artificially constructed complex systems - can induce a flow state in which actions become autonomic, occupying the mind while the body is at rest. This paper explores possible connections between these experiences, outlining a project that aims to blend the two via a technologically mediated bushwalk experience.
Does Comparative Animal Cognition Need to Be Saved by Cognitive Modeling

Colin Allen prescribes cognitive modeling as “the right kind of theory” to use in comparative animal cognition and predicts that unless researchers shift from using conceptual framework hypotheses (“the wrong kind of theory”) to cognitive models, the field will fail to be sustained or develop further. I argue, on the contrary, that the robust development of the field over the past 35 years actually belies Allen's dire prediction. What is more, there is reason to be concerned that if Allen's prescription were wholeheartedly adopted by researchers, it would undermine one of the principal aims of the field: the discovery of the reasons for which animals act. Although cognitive modeling may be a useful tool to use to verify predictions made by conceptual framework hypotheses, I see no reason to think that comparative animal cognition would be, or needs to be, saved by researchers coming to taking cognitive modeling as the right kind of theory to use in the field.
Game Theoretic Multimode Precoding Strategy Selection for MIMO Multiple Access Channels

This paper is concerned with decentralized selection of multimode precoding strategy for multiple-input multiple-output (MIMO) multiple access channels. We formulate it as a discrete noncooperative game. This game is shown to possess at least one pure strategy Nash equilibrium (NE) and the optimal strategy profile which maximizes the sum rate constitutes a pure strategy NE. Then we propose a decentralized algorithm based on learning automata to achieve the NE. A repeated mechanism is introduced to improve the sum rate performance and a mechanism for adapting step size is designed to control the convergence speed. Simulation results show that the proposed algorithm, which only requires limited feedback, can achieve near optimal or optimal sum rate performance.
AUTOMATIC CANCER DIAGNOSTIC DECISION SUPPORT SYSTEM FOR GENE EXPRESSION DOMAIN By

DEDICATION To my beloved and infinitely supportive wife, Kristina, and to my parents: my mother, Elena Feofilova, and my father, Roman Statnikov ii ACKNOWLEDGEMENTS First of all, I would like to acknowledge my academic advisors, Dr. Constantin F. Aliferis and Dr. Ioannis Tsamardinos, for their contribution to my Master's project. In addition, I am grateful to Dr. Aliferis for introducing me to the fields of Biomedical Informatics and Machine Learning; training me both a researcher and as a professional scientific programmer; and setting up a framework for my future research and career development. I am also indebted to Dr. Tsamardinos for providing me with excellent technical and scientific ideas that are relevant for my professional and scientific growth. I would also like to thank everybody with whom I had pleasure to work during this project. In particular, I would to express my gratitude to Dr. Douglas P. Hardin and Dr. Shawn Levy who being members of my Master's committee contributed not only to this project, but also to the journal manuscript based on this work. I would like to acknowledge all Biomedical Informatics faculty and graduate students for their countless contributions to the success of this project. Finally, I am forever indebted to my wife, Kristina Statnikova, for her understanding, endless patience and encouragement. This project would not be possible without her support.
On the Angular Resolution Limit for Array Processing in the Presence of Modeling Errors

In this correspondence, we study the impact of modeling errors on the angular resolution limit (ARL) for two closely spaced sources in the context of array processing. Particularly, we follow two methods based on the well-known Lee and Smith's criteria using the Cramér-Rao lower bound (CRB) to derive closed-form expressions of the ARL with respect to (w.r.t.) the error variance. We show that, as the signal-to-noise ratio increases, the ARL does not fall into zero (contrary to the classical case without modeling errors) and converge to a fixed limit depending on the method for which we give a closed-form expression. One can see that at high SNR, the ARL in the Lee and Smith sense are linear as a function of the error variance. We also investigate the influence of the array geometry on the ARL based on the Lee's and Smith's criteria.
Power quality analysis of multilevel grid-interactive converter system with varying DC source and switching angle

This paper aims to present the power quality analysis of Multilevel Inverter (MLI) phase controlled systems. The analysis is achieved by developing models for five-level MLI systems in continuous conduction mode. In this mode, the switching angle of the thyristor is varied in order that it can be operated in inversion mode. As compared to conventional line commutated DC-AC inverters which have higher order harmonics, the proposed MLI system has output with reduced higher order harmonics. In addition, the performance of proposed system has been tested at Resistance Inductance DC source (RLE) load, with changing DC voltage levels. Furthermore, the operation of proposed topology has been demonstrated under changing switching modes. It has been analyzed that the level of Total Harmonic Distortion (THD) is reduced whereas, the real output power is injected to utility-grid. Output waveforms with low harmonic content are desirable in MLI systems. The simulation models developed are well suited for practicing engineers, who are keen to their pursue studies in power quality, especially while integrating any renewable energy technology into the higher level MLI systems.
Drift robust non-rigid optical flow enhancement for long sequences

It is hard to densely track a nonrigid object in long term, which is a fundamental research issue in the computer vision community. This task often relies on estimating pairwise correspondences between images over time where the error is accumulated and leads to a drift issue. In this paper, we introduce a novel optimization framework with an Anchor Patch constraint. It is supposed to significantly reduce overall errors given long sequences containing non-rigidly deformable objects. Our framework can be applied to any dense tracking algorithm, e.g. optical flow. We demonstrate the success of our approach by showing significant error reduction on 6 popular optical flow algorithms applied to a range of real-world nonrigid benchmarks. We also provide quantitative analysis of our approach given synthetic occlusions and image noise.
Kalman Temporal Differences

Because reinforcement learning suffers from a lack of scalability, online value (and Q-) function approximation has received increasing interest this last decade. This contribution introduces a novel approximation scheme, namely the Kalman Temporal Differences (KTD) framework, that exhibits the following features: sample-efficiency, non-linear approximation, non-stationarity handling and uncertainty management. A first KTD-based algorithm is provided for deterministic Markov Decision Processes (MDP) which produces biased estimates in the case of stochastic transitions. Than the eXtended KTD framework (XKTD), solving stochastic MDP, is described. Convergence is analyzed for special cases for both deterministic and stochastic transitions. Related algorithms are experimented on classical benchmarks. They compare favorably to the state of the art while exhibiting the announced features.
A Rigorous Revisit to the Partial Distortion Theorem in the Case of a Laplacian Source

This letter studies rigorously the partial distortion theorem in the case of a Laplacian probability density function and proves that, while essentially each cell of a minimum mean-square error nonuniform scalar quantizer contributes to distortion more or less the same as its neighbor, each outer cell contributes slightly more than its inner neighbor. Also it is proved that the outermost cell distortion cannot exceed asymptotically 1.914 times that of the innermost cell. Thus, this letter clarifies in the Laplacian case the meaning of approximate equidistortion stated in the partial distortion theorem.
Design and implementation of wireless power monitoring system for public buildings

This paper represents the system design and implementation of a wireless power monitoring system for public buildings, which aims to help the country to save energy and electric power supply service providers to determine effective and efficient energy supply in urban area. Public building energy waste has been a big problem in cities and towns in China for several decades. The main reason for this is that people may forget to turn the electrical power off when leaving as the bill is not paid by them. In our monitoring system, a real time electrical power meter is used to track the operation situation, and the sensed data will be sent to the central control device through gateway. The controller will respond to the abnormal usage of electrical power due to this information. The schematic design and working procedure of each component has also been presented in this paper as well.
Efficient anytime algorithm for large-scale QoS-aware web service composition

The QoS-aware web service composition WSC problem aims at the fully automatic construction of a composite web service with the optimal accumulated QoS value. It is, however, intractable to solve the QoS-aware WSC problem for large scale instances since the problem corresponds to a global optimisation problem. That is, in the real world, traditional algorithms can require significant amount of time to finally find the optimal solution, and such an unexpected long delay is unfavourable to users. In this paper, we propose a novel anytime algorithm using dynamic beam widths for the QoS-aware WSC problem. Our algorithm generates early sub-optimal solutions and keeps improving the quality of the solution along with the execution time, up to the optimal solution if a client allows enough time. We empirically validate that our algorithm can identify composite web services with high quality much earlier than an optimal algorithm and the beam stack search.
Standing Balance, Lower Extremity Muscle Strength, and Walking Performance of Patients Referred for Physical Therapy

The purposes of this study of 30 patients referred to physical therapy were to describe the reliability of two measures of impairment and a measure of gait performance and to examine the relationships between the impairment and gait measures. The impairments measured were standing balance and muscle strength of the lower extremities, the former with a seven-level ordinal scale and the latter with a handheld dynamometer. Gait performance was measured using the seven-category scale of the Functional Independence Measure. Interday reliability was acceptable for all three measures, standing balance (weighted Kappa = .905), muscle strength (intraclass correlation coefficients = .871 to .951), and gait (weighted Kappa = .915). A Spearman correlation of . 860 was found between balance and gait measures. The correlations between the strengths of various muscle groups and gait were lower (.138 to .581). Multiple regression identified none of the strength scores as offering additional independent explanation of gait performance. Balance, as scored, appears to be a reliable and valid measure worth broader application among hospitalized patients.
Agent-Based Model of Price Competition, Capacity Choice, and Product Differentiation on Congested Networks

Using consistent agent-based techniques, this research explores the welfare consequences of product differentiation on congested networks. The economic analysis focuses on the source, evolution, measurement, and impact of product differentiation with heterogeneous users on a mixed ownership network. Path differentiation and space differentiation are defined and measured for a base scenario and several variants. The findings favour a fixed-rate road pricing policy compared to complete pricing freedom on toll roads. It is also shown that the impact of production differentiation on welfare is not always positive and depends on the level of user heterogeneity.
Handheld Person Verification System Using Face Information

This paper presents our newly developed wireless system for person verification based on the face verification technology. In our system, a handheld device cooperating with a client-server wireless network is used. Due to the limitation of the handheld device's computing power, most computations will be distributed to a remote control server. There are two main problems for implementing the system. One is the variations in lighting and background conditions. The other is that the camera on the handheld device can not be calibrated with the system in advance. For calibration on line, we use a three-point localization scheme for extracting appropriate face region according to the information of eyes and mouth. Furthermore, statistic based illumination normalization is used in preprocessing to decrease illumination influence under variant lighting conditions. Experiment shows the proposed system provides users a more flexible and feasible way to interact with the verification system through handheld device.
Skin Texture Recognition Using Neural Networks

Skin recognition is used in many applications ranging from algorithms for face detection, hand gesture analysis, and to objectionable image filtering. In this work a skin recognition system was developed and tested. While many skin segmentation algorithms relay on skin color, our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin textures. We used feed forward neural networks to classify input textures images to be skin or non skin textures. The system gave very encouraging results during the neural network generalization face.
Feature weighting and feature selection in fuzzy clustering

This paper studies the problem of weighting and selecting attributes and principal axes in fuzzy clustering. Its main contribution is a selection method that is not based on simply applying a threshold to computed feature weights, but directly assigns zero weights to features that are not informative enough. This has the important advantage that the clustering result that can be obtained on the selected subspace coincides with the projection (to the selected subspace) of the clustering result that is obtained on the full data space.
A mathematical model for the dynamics of malaria in mosquitoes feeding on a heterogeneous host population

We describe and develop a difference equation model for the dynamics of malaria in a mosquito population feeding on, infecting and getting infected from a heterogeneous population of hosts. Using the force of infection from different classes of humans to mosquitoes as parameters, we evaluate a number of entomological parameters, indicating malaria transmission levels, which can be compared to field data. By assigning different types of vector control interventions to different classes of humans and by evaluating the corresponding levels of malaria transmission, we can compare the effectiveness of these interventions. We show a numerical example of the effects of increasing coverage of insecticide-treated bed nets in a human population where the predominant malaria vector is Anopheles gambiae.
Ablation of small renal masses: practice patterns at academic institutions in the United States.

PURPOSE We aimed to determine the current practice patterns at academic institutions in the use of ablative technologies for the management of small renal masses. PATIENTS AND METHODS Mail surveys were sent to 124 academic institutions in the United States. The survey consisted of 12 questions pertaining to institutional demographic information, the use of ablation technology for small renal masses, the role of the urologist in ablation, and biopsy preferences prior to treatment. RESULTS The overall response rate was 52% (64/124). Ablation was offered by all of the academic centers that responded to the survey and included 73% percutaneous cryoablation, 52% percutaneous radiofrequency ablation, 83% laparoscopic cryoablation, and 20% laparoscopic radiofrequency ablation. Eighty-eight percent of institutions performed one to five total ablation procedures each month. Urologists alone performed 13% of ablation procedures, radiologists performed 45% of ablation procedures, and a combined approach (urologist and radiologist present) was used in 43% of the institutions. When questioned about their role during percutaneous ablation, we found that urologists were present at the time of ablation in 59% of institutions, in 32% of institutions urologists placed the needles for ablation, and in 98% of institutions urologists were responsible for the postoperative care of the patient. Eighty-nine percent of academic institutions performed a biopsy of the renal mass with 67% performing a core biopsy, 5% performing a fine-needle aspiration (FNA), and 28% performing both a core biopsy and FNA. Nineteen percent of institutions performed a renal mass biopsy prior to the day of the procedure so that the pathology was known prior to ablation. CONCLUSIONS Ablative technologies are well utilized for the treatment of small renal masses at current academic institutions with urologists directly involved in the ablation procedure in only half of the institutions. While preablation biopsy is common, pathology is rarely known prior to ablation.