Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer Simulation to Study Inflammatory Response

Systemic inflammatory response syndrome and its progression to multi-organ dysfunction syndrome represent a major challenge in the field of trauma and critical care medicine. This disease state is a product of disorders of the body’s natural response to injury. Attempts to treat this at a molecular level using information from basic science research have been unsuccessful, even detrimental. It is possible that this is due to a failure to account for the nonlinear, complex nature of the inflammatory response in formulating treatment regimes. It is proposed that agent-based computer simulation may be a way to characterize the dynamics of the inflammatory response. This article presents an abstract model of a generic tissue system. Modeling the inflammatory response as a nonlinear complex system may produce simulations that will shed light on the complex nature of the inflammatory response. In the future, more sophisticated simulations may provide a testing framework for designing and evaluating treatment regimes.
Davis Martin, Logemann George, and Loveland Donald. A machine program for theorem-proving. Communications of the ACM, vol. 5 (1962), pp. 394–397.

choices of T in the case of some theorems in elementary algebra. In one case the strategy was crucial in obtaining a proof. This strategy may be generalised so that the program need only consider a subset of the possible deductions at every level, depending on the ways in which the Herbrand expansion of S can be partitioned into consistent subsets. Choice strategies of this type (and indeed also the set of support strategy considered here) sometimes have the unfortunate consequence of excluding the shortest proof from consideration. But they greatly increase the efficiency of the proof procedure and may well provide proofs of more complicated theorems. Erratum. Page 540, line 11 from below, "alone" should read "or K3 alone. " DAVID LUCKHAM
Generalization performance of ARTMAP-based networks in structural risk minimization framework

Many techniques have been proposed for improving the generalization performance of fuzzy ARTMAP. We present a study of these architectures in the framework of structural risk minimization and computational learning theory. Fuzzy ARTMAP training uses on-line learning, has proven convergence results, and has relatively few parameters to deal with. Empirical risk minimization is employed by fuzzy ARTMAP during its training phase. One weakness of fuzzy ARTMAP concerns over-training on noisy training data sets or naturally overlapping training classes of data. Most of these proposed techniques attempt to address this issue, in different ways, either directly or indirectly. In this paper we will present a summary of how some of these architectures achieve success as learning algorithms.
ASSIMILATION OF A KNOWLEDGE BASE AND PHYSICAL MODELS OF SEA ICE TO REDUCE ERRORS IN PASSIVE-MICROWAVE CLASSIFICATIONS

An expest system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions ubn the ice classification, modifies parameters in the ice algorithm, determines a "confidence" measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing nonexpert data users with some way of assessing the usefulness of the classification results for their applications.
An Experimental Survey on Non-Negative Matrix Factorization for Single Channel Blind Source Separation

In applications such as speech and audio denoising, music transcription, music and audio based forensics, it is desirable to decompose a single-channel recording into its respective sources, commonly referred to as blind source separation (BSS). One of the techniques used in BSS is non-negative matrix factorization (NMF). In NMF both supervised and unsupervised mode of operations is used. Among them supervised mode outperforms well due to the use of pre-learned basis vectors corresponding to each underlying sources. In this paper NMF algorithms such as Lee Seung algorithms (Regularized Expectation Minimization Maximum Likelihood Algorithm (EMML) and Regularized Image Space Reconstruction Algorithm (ISRA)), Bregman Divergence algorithm (Itakura Saito NMF algorithm (IS-NMF)) and an extension to NMF, by incorporating sparsity, Sparse Non-Negative Matrix Factorization(SNMF) algorithm are used to evaluate the performance of BSS in which supervised mode is used. Here signal to distortion ratio (SDR), signal to interference ratio (SIR) and signal to artifact ratio (SAR) are measured for different speech and/or music mixtures and performance is evaluated for each combination.
MR imaging of pituitary adenomas treated with the prolactin inhibitor quinagolide

Purpose: To evaluate the volume of micro- and macroadenomas in quinagolide-treated patients with resistance to or intolerance of bromocriptine. Material and Methods: The effect of the prolactin inhibitor quinagolide on the volume of pituitary adenoma was evaluated retrospectively in 11 female patients. Prolactin levels before and after the treatment were also recorded. The indications for quinagolide therapy were side-effects of bromocriptine in 5 cases, a poor response to bromocriptine in 5 cases and both in 1 case. MR imaging with a 1.0-T magnet was performed to determine the volume reduction of the adenomas. Results: The average volume reduction of macroadenomas was 324 mm3 (46%) and that of microadenomas 73 mm3 (57%). The level of prolactin secreted by macroadenomas was reduced by an average of 163 μg/l (65%) and that by microadenomas of 113 μg (73%). In 2 microadenomas and in 1 macroadenoma, signal intensity changed during the treatment in T1-weighted images. In follow-up no changes in signal intensity were seen in 8 adenomas in non-contrast T1-weighted images. A haemorrhagic lesion was seen in 1 macroadenoma before treatment, but it disappeared during treatment. Conclusion: Quinagolide was found to be an effective alternative to bromocriptine in cases with drug intolerance or resistance, and MR imaging a suitable method for the follow-up of macro- and microadenomas.
Facial Expression Recognition from Global and a Combination of Local Features

Abstract In this paper, facial expressions are identified using contour information, along with the Gabor features extracted from highly expression-reflected facial features. We propose a novel technique to extract Gabor features from a selected region of interests. The computational complexity is reduced by a suitable selection of Gabor filters for the representation of transformed face images. Support Vector Machine classification technique is used to identify the expression that belongs to the face images.
Quora.com: Another Place for Users to Ask Questions

It’s been more than 15 years since Ewing and Hauptman wondered whether reference was an obsolete practice (1995, 3). The issue has been debated many, many times since then, and probably quite frequently leading up to the publication of their article. Whether or not reference is obsolete, there is no denying that its practice is evolving. Quora (www.quora.com) is a contemporary, web-based take on reference. Users post questions within Quora and other users answer the questions. Users can vote for and against answers (or not vote at all). It is users asking questions of friends and strangers and then sorting through the results. If the model sounds familiar, it’s because it is. There are many active question-and-answer sites, like Yahoo! Answers (answers.yahoo.com), Askville (askville.amazon.com), and Ask MetaFilter (ask.metafilter.com). Shah, Oh, and Oh (2009) defined social question and answer sites as online questioning and answering using peers. In the case of Quora, one can invite peers to answer a question, via tools like Twitter and Facebook, but questions can also be answered by users the questioner does not know. The Quora interface, which centers on a feed of questions and answers, might seem familiar to some users, because Quora was founded by two former Facebook employees (Boehret, 2011, D3). Quora lets users track questions (and their answers) by following individuals, following topics, or following specific questions. It is very similar to the Facebook News Feed concept, which has updates and information from all of a user’s contacts appearing in a single feed. The process of using Quora is simple. A user signs in and can immediately start searching for answers to questions. There are specific questions,
Improvements on Motion Estimation Algorithms in Video Coding for H.264/AVC

Motion estimation is the most important step in video compression. By using high precision motion vector in the H.264 encoder, the calculation is rapidly increased, but in the whole process of coding, motion estimation occupies about 80%. Although many motion estimation algorithms have been proposed to reduce the computational complexity of motion estimation, it still cannot meet the strict real-time demand. In this paper, based on the analysis of UMHexagonS algorithm, dynamic searching window is chosen in the UMHexagonS algorithm, then according to the motion activity, it uses different template to reduce the motion estimation time and improve video coding efficiency. Proved by the experiments on various test sequences, compared with the UMHexagonS algorithm, the motion estimation time of the proposed algorithm average saves 17.7525% in the case of the quality of the reconstructed image and rate close. It not only reduces the complexity of the algorithm, but also improves the real-time performance of the encoder.
Gender Prediction on Twitter Using Stream Algorithms with N-Gram Character Features

The rapid growth of social networks has produced an unprecedented amount of user-generated data, which provides an excellent opportunity for text mining. Authorship analysis, an important part of text mining, attempts to learn about the author of the text through subtle variations in the writing styles that occur between gender, age and social groups. Such information has a variety of applications including advertising and law enforcement. One of the most accessible sources of user-generated data is Twitter, which makes the majority of its user data freely available through its data access API. In this study we seek to identify the gender of users on Twitter using Perceptron and Nai ve Bayes with selected 1 through 5-gram features from tweet text. Stream applications of these algorithms were employed for gender prediction to handle the speed and volume of tweet traffic. Because informal text, such as tweets, cannot be easily evaluated using traditional dictionary methods, n-gram features were implemented in this study to represent streaming tweets. The large number of 1 through 5-grams requires that only a subset of them be used in gender classification, for this reason informative n-gram features were chosen using multiple selection algorithms. In the best case the Naive Bayes and Perceptron algorithms produced accuracy, balanced accuracy, and F-measure above 99%.
INTERFACING GOOGLE SEARCH ENGINE TO CAPTURE USER WEB SEARCH BEHAVIOR

The behaviour of the searcher when using the search engine especially during the query formulation is crucial. Search engines capture usersâ€™ activities in the search log, which is stored at the search engine server. Due to the difficulty of obtaining this search log, this paper proposed and develops an interface framework to interface a Google search engine. This interface will capture usersâ€™ queries before redirect them to Google. The analysis of the search log will show that users are utilizing different types of queries. These queries are then classified as breadth and depth search query. To cite this document: Fadhilah Mat Yamin and T. Ramayah, "Interfacing Google search engine to capture user web search behavior", International Journal of Electronic Commerce Studies, Vol.4, No.1, pp.47-62, 2013. Permanent link to this document: http://dx.doi. org/10.7903/ijecs.1111
Performance Assessment of a Preclinical PET Scanner with Pinhole Collimation by Comparison to a Coincidence-Based Small-Animal PET Scanner

PET imaging of rodents is increasingly used in preclinical research, but its utility is limited by spatial resolution and signal-to-noise ratio of the images. A recently developed preclinical PET system uses a clustered-pinhole collimator, enabling high-resolution, simultaneous imaging of PET and SPECT tracers. Pinhole collimation strongly departs from traditional electronic collimation achieved via coincidence detection in PET. We investigated the potential of such a design by direct comparison to a traditional PET scanner. Methods: Two small-animal PET scanners, 1 with electronic collimation and 1 with physical collimation using clustered pinholes, were used to acquire data from Jaszczak (hot rod) and uniform phantoms. Mouse brain imaging using 18F-FDG PET was performed on each system and compared with quantitative ex vivo autoradiography as a gold standard. Bone imaging using 18F-NaF allowed comparison of imaging in the mouse body. Images were visually and quantitatively compared using measures of contrast and noise. Results: Pinhole PET resolved the smallest rods (diameter, 0.85 mm) in the Jaszczak phantom, whereas the coincidence system resolved 1.1-mm-diameter rods. Contrast-to-noise ratios were better for pinhole PET when imaging small rods (<1.1 mm) for a wide range of activity levels, but this reversed for larger rods. Image uniformity on the coincidence system (<3%) was superior to that on the pinhole system (5%). The high 18F-FDG uptake in the striatum of the mouse brain was fully resolved using the pinhole system, with contrast to nearby regions equaling that from autoradiography; a lower contrast was found using the coincidence PET system. For short-duration images (low-count), the coincidence system was superior. Conclusion: In the cases for which small regions need to be resolved in scans with reasonably high activity or reasonably long scan times, a first-generation clustered-pinhole system can provide image quality in terms of resolution, contrast, and the contrast-to-noise ratio superior to a traditional PET system.
Optoelectronic implementation of diffusion neural network for contour detection

In this paper we investigate a feasibility of an opto-electronic implementation of the diffusion neural network for contour detection. The diffusion neural network performs the Gaussian operation efficiently by the diffusion process. We apply this in producing the DOG (Difference of two Gaussian) functions, which can detect the intensity changes of the different spatial frequency components in an image. In the diffusion neural network each neuron has four connections with the four nearest neighbor neurons and a self-decay loop for a 2D image, and the connection weights are fixed-valued. Therefore the diffusion neural network is simpler and more efficient than LOG masking method in hardware or optical implementation. We implement the diffusion neural network opto-electronically using the point spread function of a spatial light modulator. This system is composed of a spatial light modulator, a 2D image sensor array, and a computer. The processing time of the system is very fast. Therefore the system has a potential applicability to the system that requires a real time processing of an image.
Individualizing anaemia therapy

Individualized strategies for managing renal anaemia with erythropoiesis-stimulating agents (ESAs) need to be advanced. Recent outcomes from clinical studies prompted a narrowing of the guideline-recommended haemoglobin target (11–12 g/dL) due to increased mortality and morbidity when targeting higher haemoglobin concentrations. Maintaining a narrow target is a clinical challenge, as haemoglobin concentration tends to fluctuate. The goal of individualized treatment is to achieve the haemoglobin target at the lowest ESA dose while avoiding significant fluctuations in haemoglobin concentrations and persistently low or high concentrations. This may require changes to the ESA dose and dosing frequency over the course of treatment.
Analysis of beamformer configurations for DS-CDMA systems

Two different beamformer configurations for the base station receiver in direct-sequence code-division multiple access (DS-CDMA) systems, namely, a chip-based and a symbol-based configuration, are studied. In the chip-based configuration, different interfering components are rejected based on the spatial distribution of their power. In the symbol-based configuration, spatial diversity is exploited after despreading and different interfering components are rejected based on their interfering strength, which depends on both their power and code correlation with the signal of interest. Thus, for the symbol-based configuration, more effort is applied to rejecting the interfering components with higher interfering strength and thus a more selective and efficient system is achieved. Detailed performance analysis and simulations show that in the presence of multiple-access interference, the symbol-based configuration can lead to a significant improvement in the signal-to-interference-plus-noise ratio relative to that achieved with the chip-based configuration for both asynchronous and synchronous DS-CDMA systems.
Calibration method of absolute orientation of camera optical axis

Camera calibration is one of the most basic and important processes in optical measuring field. Generally, the objective of camera calibration is to estimate the internal and external parameters of object cameras, while the orientation error of optical axis is not included yet. Orientation error of optical axis is a important factor, which seriously affects measuring precision in high-precision measurement field, especially for those distant aerospace measurement in which object distance is much longer than focal length, that lead to magnifying the orientation errors to thousands times. In order to eliminate the influence of orientation error of camera optical axis, the imaging model of camera is analysed and established in this paper, and the calibration method is also introduced: Firstly, we analyse the reasons that cause optical axis error and its influence. Then, we find the model of optical axis orientation error and imaging model of camera basing on it’s practical physical meaning. Furthermore, we derive the bundle adjustment algorithm which could compute the internal and external camera parameters and absolute orientation of camera optical axis simultaneously at high precision. In numeric simulation, we solve the camera parameters by using bundle adjustment optimization algorithm, then we correct the image points by calibration results according to the model of optical axis error, and the simulation result shows that our calibration model is reliable, effective and precise.
ARTIFICIAL NEURAL NETWORKS AND FUZZY APPROACHES IN REMOTELY SENSED DATA ANALYSIS

ABSTRACT Artificial Neural Networks (ANN) have proved to be a great success in their applications in every branch of civil engineering. Specifically in hydrology and Remotely Sensed Data Analysis (RSDA) the applications have been numerous and offered far superior results than the traditional statistical models and methods. But, most of the applications so far, be it in hydrology or RSDA, ANNs have been limited to commonly three (or four) layered structure, with log-sigmoid (or hyper-tangent) activation functions and back-propagation learning algorithm. Recently it is being felt that there is a need to go beyond these limited capabilities and find more complex structures, better training algorithms, improved parallel processing, automated learning, self organisation, etc. to truly realise the full potential of neural networks that are still very far from their expectation i.e., the biological counterparts. While ANNs are expected to utilize the power of brain like functioning, fuzzy approaches are expected to address the problem of uncertainty, ambiguity, or fuzziness that exists in natural phenomena to arrive at a tangible and most appropriate solution. Application of Fuzzy approaches in RSDA, have been relatively recent and limited. The present paper reports, a few specific problems addressed using ANN and Fuzzy approaches, specifically in RSDA.
Oracle 8: The Complete Reference

Part 1 Critical database contents: sharing knowledge and success the dangers in a relational database. Part 2 SQL-going from beginner to expert: the basic parts of speech in SQL the basics of object-relational databases basic SQLPLUS reports and commands getting text information and changing it playing the numbers dates - then, now, and the difference conversion and transformation functions grouping things together when one query depends upon another some complex possibilities building a report in SQLPLUS changing data - insert, update and delete advanced use of functions and variables DECODE - amazing power in a single word creating, dropping and altering tables and views by what authority changing the ORACLE surroundings SQLPLUS assessing remote data an introduction to P1/SQL triggers procedures implementing types, object views, and methods collectors (nested tables and varying arrays) using large objects (LOBs) in ORACLE8 snapshots using ConText for text searches configuring the ConText option advanced object-oriented concepts in ORACLE8. Part 3 The hitchhiker's guide to the ORACLE8 data dictionary. Part 4 Designing for productivity good design has a human touch performance and design the hitchhiker's guide to the ORACLE optimiser. Part 5 Alphabetical reference. Appendix: tables used in this book.
A Design of Transducer Interface Protocol for Context-aware Middleware

Context awareness technologies are based on efficient sharing of environment information of ubiquitous sensors in everyday life, and users require this awareness technologies to get quality of services. However, the application has been restricted due to its varieties of sensors and many different methods of communications. Therefore, IEEE 1451 standard has been published to interface between sensors and network layer. But it does not connect to a middleware because IEEE 1451 is for transducer standards. This paper presents a transducer and application interface protocol which connect to the context-aware middleware by defining a protocol to obtain context information using XML. We have implemented a bridge health monitoring system and railroad monitoring system in which different sensors and users` application are used to prove the efficacy of proposed interface protocols.