The extent of medical terminology and the sheer volume of medical terms, coupled with the wish to enable all medical personnel to have an access to the data, prompted an investigation of the lexical attributes of medi...
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The extent of medical terminology and the sheer volume of medical terms, coupled with the wish to enable all medical personnel to have an access to the data, prompted an investigation of the lexical attributes of medical name files. Knowledge of the lexical structure is a prerequisite for efficient coding which may provide inexpensive data storage. One particular medical name base taken from obstetrics and gynecology is analyzed, and its lexical attributes are reported. Properties are presented in tabular form, followed by a brief discussion.
A hybrid scheme for return-to-zero (RZ) to carrier-suppressed RZ (CSRZ) format conversion is proposed and experimentally demonstrated at 40 Gbit/s. A self-pulsing gain-coupled two-section distributed feedback (GC-TSDF...
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A hybrid scheme for return-to-zero (RZ) to carrier-suppressed RZ (CSRZ) format conversion is proposed and experimentally demonstrated at 40 Gbit/s. A self-pulsing gain-coupled two-section distributed feedback (GC-TSDFB) laser was used for all-optical CSRZ clock pulse generation. A receiver with a low-bandwidth electrical amplifier was used for data recovery and data coding. The converted CSRZ signal had a root-mean-squared timing jitter of 0.6 ps and an extinction ratio of 15 dB.
A new segmented group-inversion coding is proposed to achieve current balancing in single-ended parallel data transmission. With minimal increase in number of pins, the proposed coding reduces the difference between t...
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A new segmented group-inversion coding is proposed to achieve current balancing in single-ended parallel data transmission. With minimal increase in number of pins, the proposed coding reduces the difference between the number of ZEROS and ONEs to only 0 or 2. Since the proposed coding is a simple inversion-or-not transformation of pre-defined groups of binary data, it can be implemented with greatly simplified logic circuits. Generalization for the optimum grouping is also presented. A transmitter with 16-bit link was designed for verification. The proposed coding scheme is suitable for gigabit parallel links to reduce the simultaneous switching noise.
data characterizing is considered the first and main stage of the statistical analysis. Rather than characterizing each biomechanical signal through one or few global indicators, such as the mean or the root mean squa...
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data characterizing is considered the first and main stage of the statistical analysis. Rather than characterizing each biomechanical signal through one or few global indicators, such as the mean or the root mean square, this paper suggests first to cut the scale into several fuzzy windows and to summarize the data within each window through an occurrence indicator. These indicators become the analysis variables. They can be analyzed through the multiple correspondence analysis, which shows the most discriminant variables, connections between them, empirical situation classes and correspondences between these classes and the most discriminant variables. An example is considered for arguing our point of view;it concerns characterizing and analysis of forces situated at the hand, foot and back level in a load lifting task. (C) 1998 Elsevier Science Ltd. All rights reserved.
Multi-level partial response channel is investigated for submicron-trackwidth multi-track recording based on high areal density perpendicular magnetic recording. The assumed single-pole head combination is a multi-wri...
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Multi-level partial response channel is investigated for submicron-trackwidth multi-track recording based on high areal density perpendicular magnetic recording. The assumed single-pole head combination is a multi-write head of submicron-trackwidth and relatively wide single read-head. Encoding rules including nero-level magnetization for the partial response channel is proposed for the head and the channel combination. A simulation assumed ideal playback waveform and an experiments with actual heads show availability of the method.
Diagnosis is a basic issue of any fault-tolerance policy. Fault localization within the neural architecture is necessary to provide information for hardware reconfiguration in order to achieve system survival, possibl...
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Diagnosis is a basic issue of any fault-tolerance policy. Fault localization within the neural architecture is necessary to provide information for hardware reconfiguration in order to achieve system survival, possibly with reduced computational capabilities. In this paper, a comprehensive approach to architectural fault-tolerant design of neural networks is proposed and evaluated, with specific reference to concurrent high-level diagnosis and fault localization. The approach refers to the operational life of trained neural networks. Two error detection techniques are applied: on-line concurrent diagnosis with the use of data coding for error detection at neuron level and on-line compact testing for localization of the faulty neuron within the network. (C) 2002 Elsevier Science B.V. All rights reserved.
Medication exposure is an important variable in virtually all clinical research, yet there is great variation in how the data are collected, coded, and analyzed. coding and classification systems for medication data a...
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Medication exposure is an important variable in virtually all clinical research, yet there is great variation in how the data are collected, coded, and analyzed. coding and classification systems for medication data are heterogeneous in structure, and there is little guidance for implementing them, especially in large research networks and multi-site trials. Current practices for handling medication data in clinical trials have emerged from the requirements and limitations of paper-based data collection, but there are now many electronic tools to enable the collection and analysis of medication data. This paper reviews approaches to coding medication data in multi-site research contexts, and proposes a framework for the classification, reporting, and analysis of medication data. The framework can be used to develop tools for classifying medications in coded data sets to support context appropriate, explicit, and reproducible data analyses by researchers and secondary users in virtually all clinical research domains. (C) 2014 Elsevier Inc. All rights reserved.
Fields such as medicine, biomechanics or ergonomics need to measure the positions and the rotational movements of body segments. The aim of this article is to underscore the problem of imperfection on angle measuremen...
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Fields such as medicine, biomechanics or ergonomics need to measure the positions and the rotational movements of body segments. The aim of this article is to underscore the problem of imperfection on angle measurement using a three-dimensional television system. First, the error on a single angle value is assessed through the classical Taylor's formula and through a simulating approach. Then the error is considered for an entire signal through either an experimental signals, a specific coding technique is suggested. Finally, two graphical pattern are proposed th show globally the distance between the signals with regard to the error.
A methodology is presented to analyse multidimensional signals from several recording periods resulting from an experimental study on human or other living systems. The methodology is divided into two stages: intra-pe...
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A methodology is presented to analyse multidimensional signals from several recording periods resulting from an experimental study on human or other living systems. The methodology is divided into two stages: intra-period analysis and inter-period analysis. The purpose of the first stage is to highlight general trends in multidimensional signal changes and the more informative components of the signals. The purpose of the second stage is to assess the influence of environmental or individual difference factors on a given signal component that appears to be discriminant in the first stage. To take into account the multivariable state of the system and the multi-observational aspect, a multidimensional descriptive statistical approach is used. The methods are correspondence analysis and hierarchical clustering. They are illustrated through an occupational medicine application from a study of sedentary posture.
With the rapid development of information storage and networking technologies, quintillion bytes of data are generated every day from social networks, business transactions, sensors, and many other domains. The increa...
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With the rapid development of information storage and networking technologies, quintillion bytes of data are generated every day from social networks, business transactions, sensors, and many other domains. The increasing data volumes impose significant challenges to traditional data analysis tools in storing, processing, and analyzing these extremely large-scale data. For decades, hashing has been one of the most effective tools commonly used to compress data for fast access and analysis, as well as information integrity verification. Hashing techniques have also evolved from simple randomization approaches to advanced adaptive methods considering locality, structure, label information, and data security, for effective hashing. This survey reviews and categorizes existing hashing techniques as a taxonomy, in order to provide a comprehensive view of mainstream hashing techniques for different types of data and applications. The taxonomy also studies the uniqueness of each method and therefore can serve as technique references in understanding the niche of different hashing mechanisms for future development.
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