Miracle-dz/UniFAR-FTUs huggingface dataset:
Subject and Citation Indexing. Part I: The Clustering Structure of Composite Representations in the Cystic Fibrosis Document Collection. Part II: The Optimal, Cluster-Based Retrieval Performance of Composite Representations.

The presence of clustering structure in the cystic fibrosis (CF) Document Collection is evaluated as a function of the exhaustivity of five composite representations. The composite representations are constructed from two subject descriptions, based on Medical Subject Headings and subheadings, and two citation indexes, based on the complete set of references in and a comprehensive set of citations to each document. Experimental results reveal observable evidence for clustering structure at all exhaustivity levels of all composite representations but also show that the evidence for clustering structure diminishes as the exhaustivity of each representation is decreased. The representation composed of references and citations shows less evidence of clustering structure at the exhaustive level but more uniform evidence of clustering structure over a wide range of exhaustivity levels than composite representations that include subject descriptions. The structures imposed on the CF Document Collection by all composite representations satisfy the necessary condition for a meaningful clustering outcome. © 1991 John Wiley & Sons, Inc.
NUMERICAL SIMULATION OF COUPLED HEAT TRANSFER CHARACTERISTICS FOR FLOWS AT SUPERCRITICAL PRESSURE

This article describes a numerical model to simulate the flow and heat transfer at supercritical pressure of fluid. A real-fluid model for thermophysical properties, such as density, enthalpy, specific heat, viscosity and thermal conductivity is implemented. The numerical validation of this proposed model, in conjunction with radiation and conjugate heat transfer models, is carried out for the coupled heat transfer against the experimental measurement of Jet-A and SF{sub 6} at high pressures. The satisfactory comparison between prediction and measurement is obtained.
A new serial sensing approach for multistorage non-volatile memories

This paper presents a novel serial sensing method for multistorage non-volatile memories. The method is based on a dichotomic algorithm to detect the level stored in the memory cell selected. While maintaining the main advantage of the serial approach (the use of a single sense amplifier), the method proposed also reduces to a minimum the overall time needed to read the cell content. Sensing time is independent of the memory cell content.
Information seeking behaviour of master's students using library electronic databases in the Faculty of Humanities, Development and Social Sciences of the University of KwaZulu-Natal

The purpose of this study was to investigate the use of electronic databases by master's students in the Faculty of Humanities, Development and Social Sciences (HDSS) at the University of KwaZulu-Natal, Pietermaritzburg (UKZNP) campus. The study which was based on a master's thesis aimed to establish which electronic databases master's students used and how frequently they were used. The conceptual framework for the study was rooted in Kuhlthau's Information Search Process. The methodological approach undertaken by the researcher was quantitative and data was collected using a questionnaire. The outcome of the study revealed that a majority of HDSS master's students at UKZN-P used the electronic databases and a number of problems were experienced when using the databases. Recommendations for the library include ensuring that training or user education is ongoing and meets all the various users' needs; improving students' access to the databases by limiting the need for passwords; improving the internet bandwidth to enhance the speed of connection, and using the internet and web-based services such as newsgroups, bulletin boards, Web 2.0 facilities to communicate with users.
Modular analog continuous-time VLSI neural networks with on-chip Hebbian learning and analog storage

A modular analog circuit design approach for hardware implementations of neural networks is presented. This approach is based on the use of small transconductance multipliers as the main component, and is therefore called the T-mode (transconductance-mode) approach. This circuit design technique was used to design a set of modular chips which assembled to build either BAM (bidirectional associative memory) networks, Hopfield networks, winner-take-all networks, or simplified ART1 networks. The approach is extended afterwards in order to include a Hebbian learning rule into each synapse. As an example, a learning BAM network system is shown. The experimental results given were obtained from 2- mu m CMOS double-metal double-polysilicon (MOSIS) prototypes. <<ETX>>
Receiver Design for Digital Fiber Optic Transmission Systems Using Manchester (Biphase) Coding

An analysis of the sensitivity of an optical receiver in a digital communication system using Manchester (hiphase) coding is performed. Both cases of p-i-n and avalanche photodiodes are con- sidered. Experimental results for the sensitivity of a Manchester re- ceiver operating at 250 Mbits/s are reported. Two types of low noise receiver amplifiers, namely the high impedance and the transimped- ance amplifier, are designed and implemented for use in the receiver. A receiver sensitivity of -49.8 dBm in terms of detected optical power is obtained (at a bit error rate and 0.1 laser extinction ratio), which corresponds to only 175 average photons per bit. It is shown that in contrast to the NRZ code, the Gaussian approximation theory tends to underestimate the Manchester receiver sensitivity. Tradeoffs between Manchester and NRZ coding are also discussed in terms of receiver sensitivity and ease of implementation. It is shown that Manchester coding is an attractive alternative to NRZ coding for optical transmission systems, particularly when an avalanche photo- diode is used.
Increasing the discovery power of -omics studies

Motivation: Current clinical and biological studies apply different biotechnologies and subsequently combine the resulting -omics data to test biological hypotheses. The plethora of -omics data and their combination generates a large number of hypotheses and apparently increases the study power. Contrary to these expectations, the wealth of -omics data may even reduce the statistical power of a study because of a large correction factor for multiple testing. Typically, this loss of power in analyzing -omics data are caused by an increased false detection rate (FDR) in measurements, like falsely detected DNA copy number changes, or falsely identified differentially expressed genes. The false detections are random and, therefore, not related to the tested conditions. Thus, a high FDR considerably decreases the discovery power of studies, especially if different -omics data are involved. Results: On a HapMap data set, where known CNVs have to be re-detected, I/NI call filtering was much more efficient than variance-based filtering. In particular, the I/NI call filter outperforms variance-based filters on data with rare events like the CNVs in the HapMap data set. We assessed the efficiency of the I/NI call filter in reducing the FDR on two different cancer cell lines where it reduced the FDR 18- to 22-fold. Materials and Methods: A mitigation strategy for too high FDRs is to filter out putative false detections. We suggest using probabilistic latent variable models to identify putative false detections which may be found via such models by high estimated noise or by model-based measurement inconsistencies across samples. To select such a model, a Bayesian approach starts with the maximum a priori model that assumes no detection and selects the maximum a posteriori model. Hence detection results in a deviation of the maximal posterior from the maximal prior model measured by the information gain obtained by the data. If this information gain exceeds a threshold then the selected model obtains an Informative/Non-Informative (I/NI) call that indicates a detection. I/NI call filtering has been successfully applied in different projects, but it has so far not been shown that correction for multiple testing after I/NI call filtering still controls the type-I error rate. We prove this important property of the I/NI call and show that it is independent of commonly used test statistics for null hypotheses. We apply the I/NI call to transcriptomics (gene expression), where the prior model corresponds to a constant gene expression level across compared samples, and to genomics, analyzing copy number variation (CNV) data, where the prior model corresponds to a constant DNA copy number of 2 across compared samples.
Protection of Windows Media Video Providing Selective Encryption

As content serviced for IP set-top boxes is streamed over IP network, the existing hacking tools for IP network can be used to capture the streamed content. Until recently, most of the content serviced on IP set-top boxes has been MPEG-2 TS. However, this content will be gradually moved to WMV, MPEG-4 or H.264 because of the relatively low compression efficiency and overhead of the TS packet. In this paper, we propose a DRM scheme other than WMRM for streamed WMV content. Our approach is to design a DRM scheme independent to the existing WMV streaming system. We also design this scheme in order to provide the feature for controlling the DRM processing time considering device performance. We verified it through the experiment.
Applied Information Technology in Graphics Algorithm Implementation Based on the Web Canvas

The canvas in the HTML5 provides very powerful ability to realize complex graphics and image operations. It can be used for developing information application about graphics such as chart module, scientific computing visualization, drawing software, animation system and information visualization and so on. It will play an important role in the web game for PC or mobile platform because the HTML5 has the platform-independent feature. In this paper a system of graphics algorithm presentation is provided and it uses the prototype object and image data structure of canvas rendering context 2D model to define the custom function to implement the graphics algorithm. It demonstrates the realization process of the principle of graphics algorithms and it shows that the canvas has great flexibility and scalability characteristics.
Design of cellular production systems A graph-theoretic approach

SUMMARY A method is presented for forming machine cells while implementing group technology. Information derived from the route cards of the components is analysed and the situation is represented in the form of a graph whose vertices correspond to the machines and whose edges represent the relationships created between the machines by the components using them. For finding the cells a graph partitioning approach is suggested and developed. Results obtained from testing the method using actual data are also presented.
An Integrated Voice-Data Communication System for VHF Links

In this work, a combined amplitude-phase modulation communication system is considered. Amplitude modulation is used to transmit a voice signal, and phase modulation is used for data transmission. Such a scheme was studied as a possible realization of a data channel between aircraft and ground station, which can be introduced without great modifications of the actual on-board equipment. The performance of the combined modulation system is evaluated through a computer simulation.
Fast Fourier Transforms on Energy-Efficient Application-Specific Processors

Many of the current applications used in battery powered devices are from digital signal processing, telecommunication, and multimedia domains. Traditionally application-specific fixed-function circuits have been used in these designs in form of application-specific integrated circuits (ASIC) to reach the required performance and energyefficiency. The complexity of these applications has increased over the years, thus the design complexity has increased even faster, which implies increased design time. At the same time, there are more and more standards to be supported, thus using optimised fixed-function implementations for all the functions in all the standards is impractical. The non-recurring engineering costs for integrated circuits have also increased significantly, so manufacturers can only afford fewer chip iterations. Although tailoring the circuit for a specific application provides the best performance and/or energy-efficiency, such approach lacks flexibility. E.g., if an error is found after the manufacturing, an expensive chip iteration is required. In addition, new functionalities cannot be added afterwards to support evolution of standards. Flexibility can be obtained with software based implementation technologies. Unfortunately, general-purpose processors do not provide the energy-efficiency of the fixed-function circuit designs. A useful trade-off between flexibility and performance is implementation based on application-specific processors (ASP) where programmability provides the flexibility and computational resources customised for the given application provide the performance. In this Thesis, application-specific processors are considered by using fast Fourier transform as the representative algorithm. The architectural template used here is transport triggered architecture (TTA) which resembles very long instruction word machines but the operand execution resembles data flow machines rather than traditional operand triggering. The developed TTA processors exploit inherent parallelism of the application. In addition, several characteristics of the application
Searching relationships between enterprise websites using graph based web crawling

The objective of this paper is to find explicit web relationships using enterprise websites as seeds. We apply a web crawler to find these relationships in a hierarchy starting from the given seed using the external links to construct a Jaccard Score weighted tree. The proposed methodology aims to search related enterprises from the root node based on the link, which are potential partners, suppliers, clients, etc. We crawl the whole site to find external links using the Breadth First Search (BSF) algorithm and build a tree structure containing just the interesting external links. The applied algorithms were programmed with very simple computational components and may produce interesting results to analyze the domain of sites, their structure, and how they link with each other in their acting range.
Research of Online Intelligent Question Answering System Based on Curriculum Domain Ontology

At present question answering system mostly take the keyword matching as the foundation, it has ignored the keywords itself contains semantic information, and the keyword matching accuracy is low. But the intelligent question answering system is on this basis, it added the understanding to the semantic relations. In the article we proposed the intelligent question answering system based on curriculum domain ontology, it can significantly enhance the recall and precision of the information retrieval by the semantic inference.
A freehand sketchy graphic input system: SketchGIS

Sketching is a natural and effective way to capture designer's brainstorms ideas. This paper presents a sketch-based graphics input system for conceptual design (SketchGIS), which is mainly based on online graphic recognition and dynamic user modeling. Online graphic recognition can discover latent primitive shapes among user-drawn strokes and show the regularized shape on the screen immediately based on spatial-relation graph (SRG) representation and conditioned partial matching by shape preparing, feature recognition, shape filtering and regularization. Dynamic user modeling method is used to recognize and predict sketchy composite shapes before they are completely drawn for user adaptation, which is based on the SVM-based incremental active learning method and the incremental decision tree induction method. Experiments show that the proposed method in this paper can yield good recognition precision, and the prototype system proposed provides fine user interaction effect, especially for UML diagramming.
Learning Summarization by Using Similarities

Summarization is an important skill that many of us need. Yet, this skill must be learned. This is why it is taught as a part of composition courses in language programs. The final goal of our research project is to design a system to help students to learn to summarize French texts by using a method called Case-Based Reasoning (CBR). Such a system uses previous, similar situations in order to make a new summary by reusing and adapting, if necessary, the same summarization rules. It then saves the new case—the input text, its summary and the applied summarization rules—which will serve for future, analogous situations. Therefore, each time the system builds a summary, an example of the summarization process is created. One can learn how to make a summary by observing the system's method of summarization, and by getting the system-generated explanations which accompany the process. This paper explores this new research topic and describes the rationale underlying the learning of text summarization by using.
A method for scale parameter selection and segments refinement for multi-resolution image segmentation

Image segmentation is the basis of object-based information extraction from remote sensing imagery. Image segmentation based on multiple features, multi-scale, and spatial context is one current research focus. The scale parameters selected in the segmentation severely impact on the average size of segments obtained by multi-scale segmentation method, such as the Fractal Network Evolution Approach (FNEA) employed in the eCognition software. It is important for the FNEA method to select an appropriate scale parameter that causes no neither over- nor undersegmentation. A method for scale parameter selection and segments refinement is proposed in this paper by modifying a method proposed by Johnson. In a test on two images, the segmentation maps obtained using the proposed method contain less under-segmentation and over-segmentation than that generated by the Johnson’s method. It was demonstrated that the proposed method is effective in scale parameter selection and segment refinement for multi-scale segmentation algorithms, such as the FNEA method.
Comparison of routing protocols in mobile ad-hoc wireless networks

Routing protocols for Mobile Ad-Hoc Wireless Networks are faced with challenges such as sequential topology variation, low transmission power and asymmetric connections. It has been proved that both proactive and reactive protocols are non-functional with these conditions. Zone Routing Protocol (ZRP) blends the proactive and reactive protocols benefits and the zone topology plan for each node is kept in it timely. In this work, the zone routing protocol is implemented and compared with proactive and reactive protocols which the experiment results are presented. Keywords: Mobile ad-hoc wireless networks, Proactive protocol, Reactive protocol, Zone routing protocol;
A computational theory of executive cognitive processes and multiple-task performance: Part 2. Accounts of psychological refractory-period phenomena.

Abstract : Further simulations of multiple task performance have been conducted with computational models that are based on the Executive Process Interactive Control (EPIC) architecture for human information processing. These models account well for patterns of reaction times and psychological refractory period phenomena (delays of overt responses after short stimulus onset asynchronies) in a variety of laboratory paradigms and realistic situations. This supports the claim of the present theoretical framework that multiple task performance relies on adaptive executive control, which enables substantial amounts of temporal overlap among stimulus identification, response selection, and movement production processes for concurrent tasks. Such overlap is achieved through optimized task scheduling by flexible executive processes that satisfy prevailing instructions about task priorities and allocate limited capacity perceptual motor resources efficiently.
Spatial detection of tv channel logos as outliers from the content

This paper proposes a purely image-based TV channel logo detection algorithm that can detect logos independently from their motion and transparency features. The proposed algorithm can robustly detect any type of logos, such as transparent and animated, without requiring any temporal constraints whereas known methods have to wait for the occurrence of large motion in the scene and assume stationary logos. The algorithm models logo pixels as outliers from the actual scene content that is represented by multiple 3-D histograms in the YCBCR space. We use four scene histograms corresponding to each of the four corners because the content characteristics change from one image corner to another. A further novelty of the proposed algorithm is that we define image corners and the areas where we compute the scene histograms by a cinematic technique called Golden Section Rule that is used by professionals. The robustness of the proposed algorithm is demonstrated over a dataset of representative TV content.
Mixed memory model for image processing and modeling with complex Daubechies wavelets

In this paper, we propose a statistical modeling of images based on a decomposition with complex-valued Daubechies wavelets. These wavelets possess interesting properties that can be turned into account in the modeling to obtain a better characterization of the images. This characterization is achieved by statistically modeling the wavelet coefficient distribution via hidden Markov tree model. The wavelet coefficients in an image are organized into three tree structures and this type of model has already been used successfully in this context by independently modeling each of these trees. We propose a further refinement by considering the joint modeling of the three trees with a so- called mixed memory hidden Markov tree model. The mode is base don a memory mixture, a general approach to obtain an approximation of the joint distribution in the presence of factorial Markov models. The utilization of such model s is quite general and can be applied to various signal- processing problems. To illustrate the interest of this model as well as the relevance of using complex Daubechies wavelets, we evaluate their performance for a classification and a denoising application.
An algorithm for dynamic processing of dawg's

SCOPE: Algorithms, Information storage and retrieval. A trie is a search tree obtained by merging the common suffixes of the key set. It has the advantage that all keys as prefixes of an input string can be retrieved with high speed. When the size of the key set is enlarged, however, a problem arises, as the number of transitions increases, so too does the need for a large storage capacity. This paper proposes an algorithm that dynamically constructs DAWGs (Directed Acyclic Word Graphs) for the handling of dynamic key sets. It also solves the problem of the increasing number of transitions in the trie structure. The proposed method constructs a DAWG through the local separation of common suffixes for updating a key and, after finishing updating a key, the local transition merge of common suffixes. The proposed algorithm is theoretically evaluated and the data structure for the implementation is discussed. Experimental results show that the number of transitions in the DAWG is reduced by approx. 50 to 70% .