Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Enhancement Algorithm Based on Zone System and Dual-Exposure Techniques

Abstract Luminance is crucially important to the quality of images. Colour, details, and texture can be washed out when luminance is exceedingly bright or hidden when luminance is overly dark. Logarithmic and gamma transformations are two well-known methods to alter exposure values. Unfortunately, both of these methods involve compressing the dynamic range of the image. This paper proposes a simple method based on the zone system devised for film photography to provide two levels of image compensation for the adjustment of luminance. The zone system is used to determine the level luminance, whereupon two compensation strategies are applied to produce an optimized high key or low key images. Experimental results demonstrate the superior performance of the proposed compensation method over existing methods, according to the evaluation using histograms, contour plots, the universal quality index, and structural similarity.
HIV/AIDS-related information needs of urban and rural residents of northwest Ethiopia: alerting the rural populace and meeting the progressive needs of the urban populace

Urban and rural areas in sub-Saharan Africa are characterized by different HIV/AIDS epidemiological and socio-ecological contexts. Against a backdrop of such variations, the present study assessed the impacts of urbanity vs. rurality on HIV/AIDS-related information needs. Cross-sectional survey data were gathered from 995 respondents in northwest Ethiopia. The findings indicated that urban residents’ concern about and information needs on HIV/AIDS was greater than that of the rural populace. Urban and rural residents were also found to be significantly different in their preferences for specific types of HIV/AIDS-related information. While rurality was found to be associated with a preference for basic HIV transmission and prevention information, urbanity was associated with a preference for information on HIV/AIDS-related care and support. Implications for HIV/AIDS information campaigns are discussed.
Artificial Immune Systems: A New Computational Intelligence Approach

Introduction. - Fundamentals of the Immune System. - A Framework for Engineering Artificial Immune Systems. - A Survey of Artificial Immune Systems. - The Immune System in Context with Other Biological Systems. - AIS in Context with Other Computational Intelligence Paradigms. - Case Studies. - Conclusions and Future Trends. - References. - Appendix I: Glossary of Biological Terms. - Appendix II: Pseudocode for Immune Algorithms. - Appendix III: WEB Resources on Artificial Immune Systems. Index.
Visual voice activity detection with optical flow

Current voice activity detection methods generally utilise only acoustic information. Therefore they are susceptible to false classification because of the presence of other acoustic sources such as another speaker or non-stationary noise. To address this issue, the authors propose a new method of voice activity detection using solely visual information in the form of a speaker's mouth region. Such video information is not affected by the acoustic environment. Simulations show that a high percentage correct silence detection (CSD) can be obtained with a low percentage false silence detection (FSD). Comparisons with two other visual voice activity detectors show the proposed method to be consistently more accurate, and on average yields a 4% improvement in CSD. The usefulness of the method is confirmed by applying it to a previously published audio–visual convolutive blind source separation algorithm, to increase the intelligibility of a speaker.
Transforming library and higher education support services: can change models help?

Purpose – The purpose of this article is to analyse an organisational change process that sought to integrate library and other educational support services in an Australian university.Design/methodology/approach – The article assesses the organisational change processes using John Kotter's eight step approach as outlined in his book Leading Change.Findings – While the change processes enjoyed varying degrees of success, it is revealed that several of the techniques recommended by Kotter in his eight steps were adopted, but that the process did not fully utilise the entire eight step process. Questions surrounding the suitability of organisational change models are also raised.Research limitations/implications – The successful outcomes from the change processes owe credit to Kotter's model for organisational change. While models for change may have certain limitations, they are still revealed as useful in the hands of a skilful leader.Practical implications – Kotter's eight step model is reviewed in the c.
A Dynamic Malware Detection Approach by Mining the Frequency of API Calls

Dynamic detection method based on software behavior is an efficient and effective way for anti-virus technology. Malware and benign executable differ mainly in the implementation of some special behavior to propagation and destruction. A program's execution flow is essentially equivalent to the stream of API calls. Analyzing the API calls frequency from six kinds of behaviors in the same time has the very well differentiate between malicious and benign executables. This paper proposed a dynamic malware detection approach by mining the frequency of sensitive native API calls and described experiments conducted against recent Win32 malware. Experimental results indicate that the detection rate of proposed method is 98% and the value of the AUC is 0.981. Furthermore, proposed method can identify known and unknown malware.
Discriminating brain activated area and predicting the stimuli performed using artificial neural network

classifying fMRI paradigms. The classifier’s performance was evaluated in terms of the Sensitivity and Specificity , Prediction Accuracy and the area A z under the receiver operating charac-teristics (ROC) curve. From the ROC analysis, values of A z up to 1 were obtained with 60 PCs in discriminating the visual paradigm from the auditory paradigm.
Análisis estructural de una red social en línea: la red española de Flickr

This paper intends, from a structural point of view, to analyse the network of Flickr’s members who live or were born in Spain. The aim of the study is to know how the network evolves, what is its shape, what groups are detected and what uses are carried out within the network. We identified 663 Flickr members through a double snowball process and harvested their joining date, photos and contacts with a crawler. The results show that the users who joined Flickr in 2004 use the service as a communication medium among amateur photographers, while the subsequent members utilise Flickr as a real social network, using the photos as a way to express personal experiences, opinions and tastes.
Interference cancellation for EDGE via two-user joint demodulation

EDGE has been introduced as an evolution of GSM for providing voice and high-speed data services. To cope with the ever-increasing demands on higher spectral efficiency, a tight frequency reuse (1/3 or even 1/1) may be adopted for GSM/EDGE in the foreseeable future, motivating the need to investigate advanced interference cancellation techniques. We consider joint demodulation for cancelling a dominant cochannel or adjacent-channel interferer. A complete receiver structure is described, assuming burst-synchronous users. Simulation results show that large performance gains are obtained with moderate receiver complexity in a dominant interferer-limited environment.
Active Detection of Application Layer Attacks Based on Analysis of HTTP-Session

Application layer vulnerabilities represent a substantial portion of the security exposures of computer networks. In this paper, we explore the effectiveness of HTTP-session model to effectively describe web access behavior. HTTP-sessions are extracted from http requests as accessed by users. Based on the HTTP-session model and the analysis of web based attacks, we present an active anomaly detection framework to detect web based attacks. We demonstrate the effectiveness of the proposed methods via simulation studies using real-world web access requests. The result shows that our methods can effectively detect the application layer attacks.
Timoshenko beam-solution in terms of integrated radial basis functions

The Indirect Radial Basis Function (IRBF) method is a mesh free method that operates on the strong form of a differential equation. It uses a point interpolation method, which makes the implementation of boundary conditions very easy. It does not require any numerical integration as the method starts with the interpolation of the highest order derivatives of the unknown function with radial basis functions. The lesser order derivatives and the function Itself are obtained using symbolic integration, which ensures no loss of accuracy. The method is used to solve the Timoshenko beam. Typical results for uniformly distributed loads are compared to similar predictions obtained from analytical solutions. Excellent agreement is obtained for a variety of boundary conditions.
Accurate Numerical Methods for Computing 2D and 3D Robot Workspace

Exact computation of the shape and size of robot manipulator workspace is very important for its analysis and optimum design. First, the drawbacks of the previous methods based on Monte Carlo are pointed out in the paper, and then improved strategies are presented systematically. In order to obtain more accurate boundary points of two-dimensional (2D) robot workspace, the Beta distribution is adopted to generate random variables of robot joints. And then, the area of workspace is acquired by computing the area of the polygon what is a closed path by connecting the boundary points together. For comparing the errors of workspaces which are generated by the previous and the improved method from shape and size, one planar robot manipulator is taken as example. A spatial robot manipulator is used to illustrate that the methods can be used not only on planar robot manipulator, but also on the spatial. The optimal parameters are proposed in the paper to computer the shape and size of 2D and 3D workspace. Finally, we provided the computation time and discussed the generation of 3D workspace which is based on 3D reconstruction from the boundary points.
Fast Initial State Assessment for State Estimator using Optimally Located Phasor Measurement Units

Complex power systems need better observability and visualization capabilities to handle critical situations effectively. Synchro-phasor measurements provide intra second visibility to power system dynamics and enable faster control actions. A Phasor Measurement Unit (PMU) measures the voltage and current phasors (angle and magnitude) at a bus in a power system. In the literature, many methods have been reported for determining a measurement set for the allocation of PMU‟s. Most of these methods use conventional optimization techniques involving more mathematical equations, which are generally time–consuming from a computation point of view, especially for large systems under emergency conditions. The operator has to take instantaneous measurements for the quick state estimation. In this paper a simplified approach has been proposed for placing the measuring devices (PMU‟s) which involves graph theoretical approach only . A linear algorithm is used to minimize the number of PMUs to monitor the entire system by modeling the system with topological observation theory. A relationship was developed between phasors where PMU‟s are located and unknown phasors of the system. The results can be used as initial assessment for the state estimator. The algorithm was tested on IEEE-14 Bus System. General Terms Phasor Measurement Units, Graph Theory
Ultrasonic classification of breast tumors based on multi-instance learning

Currently, locating the tumor ROI is the prerequisite of feature extraction. However, due to the low contrast and complex background of ultrasound images it is hard to obtain the accurate tumor ROI. Other organizations often been wrongly extracted as a tumor region, result in multi-ROI (non-tumor, tumor) in one image. As the result, the performance of tumor classification algorithms will be poor. In such case, ability to discriminate non-tumor and tumor area of classifier is of the most important. This paper proposed bag structure constructor on the basis of multi-ROI and multiple instance learning (MIL) classification algorithm is introduced to solve the above problem that has ability to discriminate non-tumor and tumor area to some extent. Experiments show that accuracy of the proposed method in such problems is 10% more than the traditional ultrasonic classification of breast tumor.
The Shared Cataloging System of the Ohio College Library Center

Development and implementation of an off-line catalog card production system and an on-lin e shared cataloging syst e m are described. In off-lin e production , average cost p e r card for 529 ,8 93 catalog cards in finished form and alphabetized for filing was 6.57 cents. An account is given of system design and equipment selection for the on-line system . File organization and pro gra ms are described, and the on-line cataloging system is discussed. The system is eas y to use , efficient, reliable, and cost beneficial.
Recent additions to SLEPc, the Scalable Library for Eigenvalue Problem computations

SLEPc is a software library for the solution of large, sparse eigenvalue problems on parallel computers. We have recently extended its functionality by incorporating a Krylov‐Schur eigensolver and a module for singular value computation. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Face Detection Methods Applied in ATM Automatic Identification System

Seeing that there are some unsafe factors in the process of ATM using,an ATM automatic identification system with extend functions was developed. As human face features are unique, face detection is added to the ATM as a method of authentication. Since face detection is a primary link of face recognition, our system adopts AdaBoost algorithm which is based on face detection. Experiment results demonstrated that the computing time of face detection using this algorithm is about 70ms, and the single and multiple human faces can be effectively measured under well environment, which meets the demand of the system.
Augmented learning – spreading your wings beyond the classroom

The dramatic advancements in technology over the last 5 years have created an environment that could support learning that surpasses anything we would have seen, experienced or imagined before. While new technologies offer considerable opportunities for improved learning, their use however has remained as a plug-on to traditional teaching methods. In this article, we discuss the impact of reinvigorating two courses where the use of Mobile Web 2.0 (MW2.0) tools was embedded within the learning process with an aim of enabling learner-generated content and context. Students and staff in this collaborative project, from two different courses, were equipped with iPhone 4s and iPad 2s for the duration of the course (n= 36, 16-week semester). A participatory action research method was used to evaluate the project and to scaffold the staff into learning and teaching in the twenty-first century. The pedagogical approach underpinning this project and the design for use of MW2.0 tools are discussed. Examples of artefacts created by the students in the project are outlined and provide an overview of the different contexts students interacted in. Keywords: Pedagogy 2.0; learner-generated content; learner-generated context; social constructivism; Mobile web 2.0 (Published: 30 August 2012) http://dx.doi. org/10.3402/rlt.v20i0. 19200
Radio System Design for Telecommunications

Preface. Chapter 1. Radio Propagation. Chapter 2. Line-of-Sight Microwave Radiolinks. Chapter 3. Digital Line-of-Sight Microwave Radiolinks. Chapter 4. Forward Error Correction and Advanced Digital Waveforms. Chapter 5. Over-the-Horizon Radiolinks. Chapter 6. Basic Principles of Satellite Communications. Chapter 7. Digital Communications by Satellite. Chapter 8. Very Small Aperture Terminals. Chapter 9. Radio System Design Above 10 GHz. Chapter 10. Mobile Communications: Cellular Radio and Personal Communication Services. Chapter 11. Wireless LANs. Chapter 12. High-Frequency (HF) Transmission Links. Chapter 13. Meteor Burst Communication. Chapter 14. Interference Issues in Radio Communications. Chapter 15. Radio Terminal Design Considerations. Appendix 1: Availability of a line-of-Sight Microwave Link. Appendix 2: References Fields and Theoretical References Converting RF Field Strength to Power. Appendix 3: Glossary of Acronyms and Abbreviations. Index.
Research of Optimizing Computer Network Based on Dynamism Theory

With the fast development of computer network services, the needs of every service is developing. To guarantee a effective computer network service we should improve the key quality of service (QoS) of each computer network service. Related QoS evaluating indexes mainly include throughput, delay time and packet loss of network. A optimizing method offers a theory support to a better computer network service quality and dynamic optimization is one of the most popular theoretical tools to study resource allocation and task scheduling problems in computer systems and computer networks. This text mainly introduces Markov decision process and Markov decision Petri nets.
Mild Aerobic Oxidation of Alcohols Catalysed by Fe2(SO4)3/4-OH-TEMPO/NaNO2

An environmentally friendly catalytic system of Fe2(SO4)3/4-OH-TEMPO/NaNO2 has been developed for aerobic oxidation of alcohols to aldehydes and ketones. The catalytic system allowed efficient and selective oxidation of a wide range of alcohols using oxygen at 1 atmospheric pressure and room temperature. 100% selectivity and excellent conversion rates were observed for benzylic alcohols and cinnamyl alcohol.
Loop Length Dependent SVM Prediction of Domain Linkers

The practical importance of the prediction of structural domains in un-annotated amino acid sequences has increased as they represent valuable targets readily characterized by high throughput methods. Here we report a support vector machine (SVM) prediction of domain linkers, which are loop regions separating two structural domains. The SVM training data set comprised 182 protein sequences from SCOP database, which contained at least one domain linker regions (all). Furthermore, the data set was divided into long (longer than 9 residues) and short (shorter than or equal to 9 residues) linker sequences. Using these data sets, we constructed three loop length dependent SVMs (SVM-All, SVM-Long, and SVM-Short), which were trained using all, long and short linkers, respectively. In addition, our new SVM input data used a position specific scoring matrix (PSSM) and predicted secondary structure information (PSS). A five-fold cross validation test indicates that the area under the ROC (receiver operating characteristics) curve (AUC) value, which represents the prediction performance, of SVM-All, SVM-Long and SVM-Short were 0.763, 0.759 and 0.759, respectively. Our previous SVMs, which used only amino acid sequence information, indicated prediction performances of 0.692, 0.702, and 0.605, for SVM-All, SVM-Long and SVM-Short respectively. The prediction performances of our new predictors thus were over 10% higher than those of our previous methods, Armadillo ( 1) (AUC value: 0.610 Dumontier et. al. J Mol Biol 2005), and neural network based method (2)(AUC value: 0.642 Miyazaki et. al. BMC Bioinformatics 2006). These results demonstrate the efficiency of our new methods. Thus, the performance has been improved by the inclusion of PSSM and PSS, in addition to sequences.
Indian Computer Science Research Output during 1999-2008: Qualitative Analysis

The paper analyses research output of computer science, in 11 sub-fields, in India during 1999-2008. The parameters studied include total research output, publications growth, citation impact, share of international collaborative publications, research communication in productive journals, characteristics of most productive institutions, authors, and high-cited papers.
[Paper] Diminished Reality for AR Marker Hiding Based on Image Inpainting with Reflection of Luminance Changes

This paper proposes a new diminished reality technique which removes AR markers from a user's view image. In order to achieve natural marker hiding, three factors should be considered; (1) naturalness of texture generated on a marker area. (2) geometric consistency between consecutive frames, (3) photometric consistency between a marker area and its surrounding. In this study, assuming that an area around a marker is locally planar, the marker area in the first frame image is inpainted using the rectified image to achieve high-quality inpainting. The unique inpainted texture is overlaid on the marker region in subsequent frames according to camera pose for temporal geometric consistency. Global and local luminance changes around the marker are reflected to the inpainted texture for photometric consistency.
Detecting and locating human eyes in segmented facial images

This paper presents a novel algorithm for automatic localization of human eyes in grayscale still images with complex background based on geometrical facial features and image segmentation,. First of all, a determination criterion of eye location is established by the priori knowledge of geometrical facial features. Secondly, a range of threshold values that would separate eye blocks from others in a segmented facial image is estimated from the facial image histogram. Thirdly, with the progressive increase of the threshold by an appropriate step in that range, the size of the existing blocks in the segmented facial image will expand, some existing blocks will merge into one block, and some new blocks will emerge. Once two eye blocks appear from the segmented image, they will be detected by the determination criterion of eye location. Finally, the 2-D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. In this way, the optimal threshold value can be automatically found based on the result of detection such that eyes can be accurately located. The experimental results demonstrate the high efficiency of the algorithm in runtime and correct localization rate.
Classification of knee problems to provide evidential support

The management of uncertainty has received much attention recently in the fields of database and artificial intelligence. Several methods of evidential reasoning have been proposed for real‐world problems with which uncertainty is associated. Considers one of these problems, that of classification, which is encountered in many domains including medicine. Focuses on a classification technique for knowledge discovery (KD). Reasoning about classifications is a primary interest in KD. Deals with obtaining evidence to confirm or refute classes. Searches for any data dependencies which exist between a classifier attribute and any of the property attributes. To illustrate the method compares a neural network classification with one based on Tanimoto’s method. It is important to note that the aim is to demonstrate this approach rather than to compare these two methods of classification. After extracting the data dependency information, employs a non‐numeric evidential reasoning method to see how well this evidence supports each of the two respective classifications.
Bradford revisited

a prescience which it would be difficult to substantiate. If, to paraphrase De Solla Price’s dictum, ninety percent of all the scientists who ever lived are alive today, then the same should be roughly true for information scientists. There certainly is, it seems to me, a great deal of talent and imagination in contemporary information work. This being recognised, it is at least interesting and perhaps instructive to reflect on those issues that concerned