Miracle-dz/UniFAR-FTUs huggingface dataset:
Predict Pregnancy Outcomes in the COVID-19 Pandemic Using Electronic Health Records and Machine Learning Approach

COVID-19 negatively impacts maternal health. We use national electronic health records data and machine learning techniques to recognize risk factors that are predictive of negative maternal outcomes in the pandemic. The cohort has been built with 191,403 gestations. The findings of this study will help advance the clinical decision support system for preventing negative maternal outcomes and promoting maternal health.
Converting English text to speech: a machine learning approach

The task of mapping spelled English words into strings of phonemes and stresses ("reading aloud") has many practical applications. Several commercial systems perform this task by applying a knowledge base of expert-supplied letter-to-sound rules. This dissertation presents a set of machine learning methods for automatically constructing letter-to-sound rules by analyzing a dictionary of words and their pronunciations. Taken together, these methods provide a substantial performance improvement over the best commercial system--DECtalk from Digital Equipment Corporation. In a performance test, the learning methods were trained on a dictionary of 19,002 words. Then, human subjects were asked to compare the performance of the resulting letter-to-sound rules against the dictionary for an additional 1,000 words not used during training. In a blind procedure, the subjects rated the pronunciations of both the learned rules and the DECtalk rules according to whether they were noticably different from the dictionary pronunciation. The error rate for the learned rules was 28.8% (288 words noticeably different), while the error rate for the DECtalk rules was 44.3% (433 words noticeably different). If, instead of using human judges, were required that the pronunciations of the letter-to-sound rules exactly match the dictionary to be counted correct, then the error rate for our learned rules is 35.2% and the error rate for DECtalk is 63.6%. Similar results were observed at the level of individual letters, phonemes, and stresses. To achieve these results, several techniques were combined. The key learning technique represents the output classes by the codewords of an error-correcting code. Boolean concept learning methods, such as the standard ID3 decision-tree algorithm, can be applied to learn the individual bits of these codewords. This converts the muticlass learning problem into a number of boolean concept learning problems. This method is shown to be superior to several other methods: multiclass ID3, one-tree-per-class ID3, the domain-specific distributed code employed by T. Sejnowski and C. Rosenberg in their NETtalk system, and a method developed by D. Wolpert. Similar results in the domain of isolated-letter speech recognition with the backpropagation algorithm show that error-correcting output codes provide a domain-independent, algorithm-independent approach to multiclass learning problems.
Note on generalization, regularization and architecture selection in nonlinear learning systems

The author proposes a new estimate of generalization performance for nonlinear learning systems called the generalized prediction error (GPE) which is based upon the notion of the effective number of parameters p/sub eff/( lambda ). GPE does not require the use of a test set or computationally intensive cross validation and generalizes previously proposed model selection criteria (such as GCV, FPE, AIC, and PSE) in that it is formulated to include biased, nonlinear models (such as back propagation networks) which may incorporate weight decay or other regularizers. The effective number of parameters p/sub eff/( lambda ) depends upon the amount of bias and smoothness (as determined by the regularization parameter lambda ) in the model, but generally differs from the number of weights p. Construction of an optimal architecture thus requires not just finding the weights w/sub lambda /* which minimize the training function U( lambda , w) but also the lambda which minimizes GPE( lambda ). <<ETX>>
Cell loss effect on QoS for MPEG video transmission in ATM networks

This paper presents our study on the effects of cell loss on QoS for the MPEG video transmission in ATM networks. A new evaluation method for the cell loss behavior of ATM networks due to congestion is proposed. The method uses a real MPEG video sequence as the input source and the MPEG video data is packetized into ATM cells. A cell discard process model called the Gilbert model is used to generate a cell discard pattern. The pattern represents the occurrences of ATM lost cells due to buffer overflow in multiplexers, Finally, the effects of cell loss on QoS is evaluated by de-packetizing (assembling) the resultant ATM cells back into MPEG video data, The QoS evaluations presented in this paper include subjective and objective evaluations of video quality under different network conditions. The evaluation results show that the effects of cell loss on QoS for MPEG video transmission in ATM networks depend on factors such as the burst cell loss length and the MPEG coding modes used.
High Frame Rate Electrical Impedance Tomography System for Monitoring of Regional Lung Ventilation

This paper describes the development of a compact high frame rate passive electrical impedance tomography system. The injected current amplitude and frequency can be adjusted to fit any EIT application. Measured results show that the system is capable of high frame rate of 89 fps and has power consumption of 1.7 W. It has automatic gain control that reduces noise and improves the quality of the measured EIT image. A comparison is made with other EIT systems to show the potential of the developed system. Clinical Relevance— The developed EIT system has application in the clinical assessment of neonatal and SARS-Co V-2 patients. In these applications there is an urgent need for a low cost bedside non-invasive imaging system to continuously monitor dynamic changes in regional lung ventilation
Séparation des niveaux de vigilance, à partir d'un signal EEG par les cartes auto-organisatrices de Kohonen

Plusieurs etudes ont deja ete menees pour tenter de discriminer, a l'aide de reseaux de neurones artificiels, les differents etats de vigilance d'un sujet humain. Dans ce papier, nous presentons en detail une methode de separation des niveaux de vigilance, a partir d'un signal EEG par les cartes auto-organisatrices de Kohonen. Nous y avons associe des le debut des medecins dont l'expertise nous a ete precieuse pour le recueil des donnees et la mise au point de notre modele.
Language difficulties in first year Science - an interim report

A key goal of the study entitled ‘A cross-disciplinary approach to language support for first year students in the science disciplines’, funded by the Carrick Institute for Learning and Teaching in Higher Education, is to examine the role of language in the learning of science by first-year university students. The disciplines involved are Physics, Chemistry and Biology. This national project also aims to transfer active learning skills, which are widely used in language teaching, to the teaching of science in first year. The paper discusses the background to the study, reports on some of the preliminary results on the language difficulties faced by first year student cohorts in science from data collected in 2008, and describes the framework we have established for the organization and delivery of first year science courses to be implemented in semester one 2009.
Signal estimation for interference cancellation and decision feedback equalization

A signal estimation device for antipodal signals is derived which is optimal in the sense of minimizing the mean square estimation error. It is applied to estimate the interfering signal components in a received signal in order to cancel them to improve the detection performance. It is shown, that especially for bad signal-to-noise ratios, the optimum device, which delivers a soft value for feedback, improves the quality of interference elimination compared to the standard two point characteristic (sign-function=hard feedback). The performance enhancement using the optimum device is investigated in two possible applications: interference cancellation for CDMA signals and decision feedback equalization for signals in frequency selective channels. A considerable gain is achieved in the first case whereas in the latter case it is only marginal. This fact is explained theoretically.
Scheduling and code generation for parallel architectures

Automatic partitioning, scheduling and code generation are of major importance in the development of compilers for massively parallel architectures. In this thesis we consider these problems, propose efficient algorithms and analyze their performances for automatic scheduling and code generation. In the first part of this thesis, we consider compile-time static scheduling when communication overhead is not negligible. We provide a new quantitative analysis of granularity issues to identify the impact of partitioning on optimal scheduling. We propose a new algorithm for scheduling on an unbounded number of processors named DSC, which outperforms existing algorithms in both complexity and performance. Furthermore, we study algorithms for scheduling on a bounded number of processors based on a multistep approach. We use DSC to cluster tasks and then use a load balancing and physical mapping heuristic to map the clusters onto processors. Finally we introduce a new task ordering algorithm that tries to minimize parallel time and overlap communication with computation. What distinguishes our approach with that of others in the literature is the low complexity and very good performance. We present theoretical and experimental results to verify the performance of these algorithms. In the second part of the thesis, we consider the code generation problem for message passing architectures. We propose a new optimized method for code generation in executing a schedule of an arbitrary task graph based on an asynchronous communication model. We optimize the code by reducing communication overhead, eliminating redundant communication and improving memory utilization. We present a correctness analysis of the generated code to assure data coherence and deadlock-free communication. We also present a new multicasting algorithm for a hypercube that eliminates unnecessary routing processors. We have implemented a compiler tool system named PYRROS that integrates the above algorithms for scheduling and code generations. The input of this system is a C program with annotated dependence information and the output is optimized parallel C code for nCUBE-I, nCUBE-II and iPSC/860 machines. The experimental results show that the performance of automatically produced code is comparable with that of hand-written code.
Analysis of the Dialysis Dose in Different Clinical Situations: A Simulation-Based Approach

This led to development of several HD schedules proposals based on the variation of the session time duration (TD) as well as on its weekly frequency (Fr). However, more fre‐ quent HD schedules require new indexes to measure the delivered dose. In this context, the Equivalent Renal Clearence (EKR) [Casino y Lopez] [3] and Standard Kt/V (stdKt/V) [Gotch] [4] indexes have been proposed to quantify the dialysis dose for different HD frequency schedules.
Cache-aware network-on-chip for chip multiprocessors

This paper presents the hardware prototype of a Network-on-Chip (NoC) for a chip multiprocessor that provides support for cache coherence, cache prefetching and cache-aware thread scheduling. A NoC with support to these cache related mechanisms can assist in improving systems performance by reducing the cache miss ratio. The presented multi-core system employs the Data-Driven Multithreading (DDM) model of execution. In DDM thread scheduling is done according to data availability, thus the system is aware of the threads to be executed in the near future. This characteristic of the DDM model allows for cache aware thread scheduling and cache prefetching. The NoC prototype is a crossbar switch with output buffering that can support a cache-aware 4-node chip multiprocessor. The prototype is built on the Xilinx ML506 board equipped with a Xilinx Virtex-5 FPGA.
Sprzętowy układ do estymacji siły oraz zmęczenia mięśni na podstawie sygnału elektromiograficznego

This paper presents an FPGA implementation of the muscle force and fatigue estimation unit based on the analysis of an electromyography (EMG) signal measured with a two-channel amplifier and the joint position measured with a quadratic encoder. The contemporary systems use the root mean square (RMS) of the EMG signal and muscle length to estimate the contraction force and decrease in the median frequency of the EMG signal to detect the muscle fatigue [2]. The proposed system consists of (Fig. 1): an infinite impulse response (IIR) high-pass filter with the cut-off frequency of 10 Hz, a dedicated RMS calculation block for the 512 samples window (Fig. 2.), the Fast Fourier Transform (FFT) block and a MicroBlaze processor. The muscle length is estimated using measurements from the encoder placed on the joint. The mean value of the EMG signal frequencies is used as the approximation of the median-frequency. The system was tested using the Xilinx SP605 evaluation kit and the obtained results were verified. The resources usage is presented in Table 1. Due to the FPGA inherent ability to parallelize computation, additional measurement channels can be easily added without increase in the processing time. The presented system is portable and can be used as a part of any mobile solution requiring feedback from the muscles-state (e.g. exoskeleton). Due to its scalability, it can be easily extended into a larger muscle-analysis system. Moreover, it can be modified to facilitate analysis of other biomedical signals. Dr inż. Piotr KACZMAREK Od 2003 pracuje na Politechnice Poznańskiej. W 2009 obronił pracę doktorską z zakresu biocybernetyki. W pracy badawczej zajmuje się zagadnieniami analizy sygnałów biomedycznych, sterowania ruchem oraz tworzeniem narzędzi wspomagających rehabilitację narządu ruchu e-mail: piotr.kaczmarek@put.poznan. pl Mgr inż. Adam SCHMIDT Absolwentem kierunku Automatyka i Robotyka spec. Robotyka na Wydziale Elektrycznym Politechniki Poznańskiej. Od 2007 roku pracuje jako asystent w Instytucie Automatyki i Inżynierii Informatycznej Politechniki Poznańskiej. W swojej pracy zajmuje się głównie wykorzystaniem technik przetwarzania obrazu i inteligencji maszynowej w robotyce mobilnej, biometrii i inżynierii sejsmicznej. e-mail: adam.schmidt@put.poznan. pl
A conceptual framework for understanding photographs

Selectivity, instantaneity, and credibility are characteristics which distinguish photography from other picturing media and make our experience of photographs significantly differ ent than our experience of other pictures. Photographs ought to be interpreted by an examination of three types of contextual in formation: internal, original, and external. Pho tographs are beneficially seen as functioning analogously to certain types of language state ments: descriptive, explanatory, interpretive, ethically evaluative, aesthetically evaluative, and theoretical. These categories are a heuristic device to prompt interpretive discourse about photographs. Placement of any photograph in one or more of these overlapping categories demands supportive evidence drawn from contextual information.
Variants of the Chandy-Misra-Bryant Distributed Discrete-Event Simulation Algorithm

Abstract : We have been using variants of the Chandy-Misra-Bryant (CMB) distributed discrete-event simulation algorithm since 1986 for a variety of simulation tasks. The simulation programs run on multicomputers (message-passing concurrent computers), such as the Cosmic Cube, Intel iPSC, and Ametek Series 2010. The excellent performance of these simulators led us to investigate a family of variants of the basic CMB algorithm, including lazy message-sending, demand-driven operation with backward demand messages, and adaptive adjustment of the parameters that control the laziness. These studies were also motivated by our interest in scheduling strategies for re-active (message-driven) multiprocess programs which are semantically similar to discrete-event (event-driven) simulators. The simulator itself is implemented in the reactive programming environment that we have developed for multicomputers: the Cosmic Environment and the Reactive Kernel. We performed the studies reported here using logic networks. Logic simulation is expected to stress a distributed simulator, and is itself of practical interest. It is easy to construct examples of logic networks with a diversity of behaviors and structural difficulties, such as large fan-in and fan-out. Low-level logic elements such as logic gates exhibit responses in which an input event may or may not influence the outputs, depending on the internal state of the element and on the states of other inputs; yet, they require very little computation to simulate their behavior. Thus, the performance results shown later in this paper involve practically no computation other than the distributed simulation itself.
Studying neural selectivity for motion using high-field fMRI

Functional magnetic resonance imaging (fMRI) offers a number of opportunities to non-invasively study the properties of the human visual system. Advances in scanner technology, particularly the development of high-field scanners, allow improvements in fMRI such as higher resolution and higher signal to noise ratio (SNR). We aimed to examine what these advances in scanner technology, combined with novel analysis techniques, can tell us about the processing of motion stimuli in the human visual cortex. In Chapter 3 we investigated whether high-resolution fMRI allows us to directly study motion-selective responses in MT+. We used event-related and adaptation methods to examine selectivity for coherent motion and selectivity for direction of motion, and examined the potential limitations of these techniques. One particular analysis technique that has been developed in recent years uses multivariate methods to classify patterns of activity from visual cortex. In Chapter 4 we investigated these methods for classifying direction of motion, particularly whether successful classification responses are based on fine-scale information such as the arrangement of direction-selective columns, or a global signal at a coarser scale. In Chapter 5 we investigated multivariate classification of non-translational motion (e.g. rotation) to see how this compared to the classification of translational motion. The processing of such stimuli have been suggested to be free from the large-scale signals that may be involved in other stimuli, and therefore a more powerful tool for studying the neural architecture of visual cortex. Chapter 6 investigated the processing of plaid motion stimuli, specifically ’pattern’ motion selectivity in MT+ as opposed to ’component’ motion selectivity. These experiments highlight the usefulness of multivariate methods even if the scale of the signal is unknown.
Using multicast in the global communications infrastructure for group communication

International Monitoring System (IMS) stations and the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization generate data and products that must be transmitted to one or more receivers. The application protocols used to transmit the IMS data and IDC products will be CD-x and IMS-x and the World Wide Web (WWW). These protocols use existing Internet applications and Internet protocols to send their data. The primary Internet applications in use are electronic mail (e-mail) and the file transfer protocol (ftp). The primary Internet communication protocol in use is the Transmission Control Protocol (TCP), which provides reliable delivery to the receiver. These Internet applications and protocol provide unicast (point-to-point) communication. A message sent using unicast has a single recipient; any message intended for more than one recipient must be sent to each recipient individually. In the current design, the IDC and the National Data Centres (NDC's) provide data forwarding to the appropriate receivers. The overhead associated with using unicast to transmit messages to multiple receivers either directly or through a forwarder increases linearly with the number of receivers. In addition, using a forwarding site introduces possible delays and possible points of failure in the path to the receivers. Reliable multicast provides communication services similar to TCP but for a group of receivers. The reliable multicast protocol provides group membership services and message delivery ordering. If an IMS station were to send its data using reliable multicast instead of unicast, only sites that are members of the multicast group would receive the data at approximately the same time. This might provide an efficient means of disseminating station data or IDC data products to all receivers and eliminate or greatly reduce the need for data forwarding. Several commercial and research reliable multicast protocols exist for the Internet. Each of these protocols is designed to serve a specific community of users and applications. The author has undertaken a study to determine if reliable multicasting is appropriate for use in the Global Communication Infrastructure (GCI).