Miracle-dz/UniFAR-FTUs huggingface dataset:
A new dc baseline stabilization scheme for neural recording microprobes

This paper presents a novel circuit methodology for rejecting the random DC drift associated with recording microelectrodes. In this approach, a sub-threshold front end MOS transistor is used as a voltage variable resistor to clamp the large, and random DC drifts at the recording site without sacrificing AC performance. A CMOS amplifier utilizing this front-end stage (along with DC common mode feedback) has been fabricated. The amplifier measures 0.18 sq. mm and has a closed loop gain of 41 dB with a power consumption of 150 /spl mu/W. The system provides -30 dB of DC attenuation, and has a CMRR of 35 dB.
Rejection of extraneous input in speech recognition applications, using multi-layer perceptrons and the trace of HMMs

In isolated-word recognition from everyday speech, a considerable share of the input lies outside the permitted vocabulary, and has to be rejected. The authors trained multilayer perceptrons to confirm or reject the choice made by a Markov model system during recognition by classifying the trace of the winning model. This rejection method is totally independent of the recognition procedure. Results show that performance on a database containing field data is better than with other rejection procedures. <<ETX>>
Graphing Calculator for Probability Students: How Was It Perceived?

Most students see Mathematics as one of the most challenging and stressful subjects, which if given an option, would rather opt out than undertake it. With low motivation and interest levels, the thought of undertaking a course in Mathematics can be worrying for some. Consequently, teachers are faced with disinterested students, who are passive in class, which makes teaching of the subject even more challenging. At times, with non participative students, Mathematics classrooms appear 'solemn'. Through the years, teachers have been experimenting or 'trying out' various approaches/techniques, in their attempt to develop students' interest and motivation. With the advent of information technology tools, teachers have now attempted to adopt more innovative approaches and incorporate ICT tools into Mathematics classrooms as well. One such tool is the graphing calculator (GC), which is adopted in this study. The incorporation of GCs into Malaysian Mathematics classrooms is at its infant stages. The study examined the students' reactions toward the incorporation of GCs into Probability lessons as well as the subject itself. Findings favor the adoption of GC in learning Probability, particularly in terms of calculator usage, quality of output, understanding of Probability concepts, confidence in solving problems, enhanced communication abilities and positive attitudes towards GC. Recommendations made aimed at assisting educators, policy-makers and researchers in enhancing the quality of the teaching and learning of Probability.
CASE: A clustering algorithm for cell formation with sequence data

Cellular manufacturing is a well-known strategy for reducing lead times in batch production systems. Most of the methods of cell formation are based on machinecomponent incidence alone. However, other factors such as production sequence and product volumes, if incorporated, can enhance the quality of the solutions. This study uses sequence data for cell-formation. A new similarity measure is defined for this purpose and appropriate measures of performance for evaluating solutions are introduced. A clustering approach of the non-hierarchical type is proposed. With new seeding techniques, the proposed algorithm clusters machines and components on the basis of sequence data. The algorithm gives encouraging results when applied to sample problems.
A tree-structured index algorithm for expressed sequence tags clustering

Expressed sequence tags (ESTs) are complementary deoxyribonucleic acid (cDNA) fragments, which are reverse transcribed from mature ribonucleic acid (mRNA), a direct gene transcript. ESTs are a readily rich information source of complete expressed gene sequences. They reveal the type and number of genes being expressed in an organism. Joining ESTs into complete gene sequences is computationally expensive because they are numerous, erroneous, redundant and mixed up. ESTs that originate from the same gene are grouped together. This enables efficient consensus sequences generation, which reveals underlying gene sequences and their possible alternative splicings. EST clustering enables efficient discovery of expressed genes based on which several fields rely such as: disease diagnostics, drug discovery, genetic engineering, alternative splicing and many others. Most clustering algorithms developed so far are quadratic and their running time is prohibitively high. A tree-structured index algorithm has been developed to efficiently cluster ESTs with respect to running time and quality of generated clusters. The algorithm clusters ESTs in a pseudometric space by recursively partitioning a data set of EST windows into two disjointed sets. Performance of the algorithm was tested with respect to running time and quality of generated clusters. Further experiments were performed to investigate the effectiveness of the triangle inequality, which was implemented to reduce distance computations during clustering. Experimental results show that the algorithm has a running time closer to linear with a 100% specificity, but it fluctuates in sensitivity. Implementation of the triangle inequality did not significantly improve the performance of the algorithm.
Reading Aloud in the Foreign Language Teaching

Some students, who attach no importance to reading aloud, believe that the reading and writing should follow the listening and speaking. However, “reading aloud” plays an important role in the English learning process. Why must we read aloud? First of all, English is a kind of phonic language, which uses the alphabetic writing. Moreover, English is a subject with practice. At the same time, “reading aloud” also is an important part in education for all-around development, which has several functions in English teaching. But in recent years, some English teachers paid more attention to the accumulation of reading skill than to reading itself, and neglected to foster the reading practice ability. Some teachers even believe that it is enough to make the students to open their mouths. In fact, reading aloud in English Teaching is very demanding.
Fractal Properties of Linux Kernel Maps

Many different measures were proposed to describe the problem of possible software complexity - the number of lines of code sometimes referred as a source lines of code (SLOC), Halstead’s volume V, McCabe cyclomatic number V(G), among others. However, any of them doesn’t take into account the possible fractal properties of software source code emerging from development process. The main aim of this paper is to show that in the case of successive Linux OS kernels fractal self-organization of the system can be seen. This is done in the relation to: (i) the analysis of rate of growth for number of files and source lines of Linux kernels code, (ii) by the presentation of some visualizations indicating self-similar graphical structure of OS kernels, (iii) by the calculations of fractal dimensions Db basing on box dimension method. Basing on obtained results it can be assumed that: (i) calculated rate of growth in the case of lines and files in the simplest approach can be approximated by the polynomial with degree 2 with R = 0.96 and R = 0.94 respectively, (ii) this system becomes more and more complex with self-similar structure, (iii) its fractal dimension is still growing. Presented analysis opens new possibilities for description of computer programs in terms of complex systems approach.
Note‐taking: A critical review

Abstract This paper aims (1) to determine why students take notes, (2) to survey the research findings available in the current literature, (3) to identify inadequacies and omissions in this literature in order to suggest more profitable lines of research for future study, and (4) to suggest guide‐lines for both teachers and students which will exploit more effectively the potential of note‐taking.
Fuzzy early discard (FED) to improve TCP Reno performance over ATM-UBR

We propose a fuzzy logic-based buffer management scheme called fuzzy early detection (FED) to improve TCP Reno performance over ATM-UBR service. FED employs the strategies of early congestion detection and selective packet discard to achieve its design goals, and adopts EPD to prevent frequent buffer overflows. Its performance is compared to that of pure EPD through simulation. The effects of TCP MSS and propagation delay on their performances are studied. Our simulation results prove that FED is superior to EPD in terms of efficiency and scalability, while its fairness remains comparable with the latter.
A 1.6-GHz CMOS PLL with on-chip loop filter

A 1.6-GHz phase locked loop (PLL) has been fabricated in a 0.6-/spl mu/m CMOS technology. The PLL consists of an LC-tank circuit, divider, phase detector with charge pump, and an on-chip passive loop filter. When the oscillator is open loop, it exhibits -115 dBc/Hz phase noise at a 600-kHz offset from the carrier. The PLL occupies an active area of 1.6 mm/sup 2/ and dissipates 90 mW from a single 3-V supply.
Developing a model and applications for probabilities of student success: a case study of predictive analytics

This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at different milestones identified. The explanatory variables, milestones and reference points when the model is run will be different at other institutions but the approach may be generalised to distance learning institutions and, more broadly, to any HE institution. Institutions, and especially distance education institutions which do not have the advantages of frequently seeing students, need to make full use of any recorded information they hold to try and identify students who are, or become, at potential risk of leaving. The importance of different factors, at different milestones, may help tailor student support to individual students and therefore improve low retention in open access distance education.
Three artificial intelligence techniques for finding the key factors in breast cancer

Abstract The advancement of medical technology has increased the amount of medical data. Data mining has become an essential tool for hospital management and medical research because it enables people to manage accumulated data and discern possible meaningful information from databases. Further medical research can thus use the important data. The current study compared 3 data mining methods, and attempted to identify the determining factors of breast cancer. The data were collected from a hospital in Taiwan and had been gathered between 2002 and 2010. Our study examined 1357 cases and 7 variables. The dataset was divided into 10 categories of training sets and testing sets. Three popular data mining algorithms (decision tree C5.0, SVM, and logistic regression) were used to predict the patients’ survival and death rates. The results showed that decision tree C5.0 outperformed both SVM and logistic regression. For training sets, the decision tree C5.0 achieved a classification accuracy of 95.8% with a sensitivity of 97.7% and a specificity of 94.7%. For testing sets, the decision tree C5.0 achieved a classification accuracy of 94.9% with a sensitivity of 95.7% and a specificity of 94.3%. The results suggested that decision tree C5.0 is the best model for prognosis in clinical practice. Our findings may provide a reference for doctors to identify new cases of breast cancer.
An Efficient Motion Estimation Algorithm for H.264/AVC

The efficient motion estimation algorithms are the important research hotspot in the real-time video coding-decoding technology. This paper proposes a novel and simple fast motion estimation algorithm based on adaptive search-pattern. The new algorithm includes three schemes: stationary block prediction, predictive search for non-stationary blocks, choosing a starting point and adaptive refinement search in merging process. Experiments show that the efficient motion estimation algorithm proposed can further reduce the computations of block-matching while improve the compression effect.
An efficient preprocessing method for suboptimal route computation

In this paper, an effective genetic‐based clustering algorithm (GCA) is proposed to preprocess the road network into a multilevel network that can reduce the route computation time substantially. Based on the multilevel network, route computation algorithms can provide suboptimal routes with little loss of accuracy (LOA). The geographic information of the road network is considered when constructing the multilevel network. In the proposed GCA, three criteria are considered to evaluate the clustering results. Route calculation results based on the multilevel network constructed by the proposed GCA are compared with the recent research to analyze and quantify the LOA. © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Are there distinct input and output buffers? Evidence from an aphasic patient with an impaired output buffer

Abstract A patient is described whose poor repetition of sentences and of lists of words contrasts with his surprisingly good performance on immediate probe recognition tasks. This result is interpreted as suggesting a distinction between a phonological input buffer involved in lexical access and, perhaps, syntactic parsing and a phonological output buffer involved in language production: the former is functioning normally and the latter is impaired. Consistent with this hypothesis, the patient does not show any comprehension impairment.
The value of replicationg the data analysis of an empirical evaluation

The aim of this research was to determine whether the results of an empirical evaluation could be confirmed using a different evaluation method. In this investigation the Qualitative Weight and Sum method used by the researchers Graf and List to evaluate several free and open source e-learning software platforms, were studied and replicated with a different method. The Analytical Hierarchy Process was used as an alternative to the Qualitative Weight and Sum method. The same input data used by the researchers Graf and List were used to replicate the evaluation. It was found that the ranking of the e-learning platforms, when using the Qualitative Weight and Sum method, differs slightly from the outcome with the Analytical Hierarchy Process method. The Analytical Hierarchy Process method has an advantage over the Qualitative Weight and Sum method in that it determines the consistency of the evaluation judgments of evaluators. Both methods are useful but it is easier to rank software using the Analytical Hierarchy Process. It was found that replication of evaluation, which was done to validate the process and results, and also to determine the consistency of evaluators was useful.
Generating Multimodal References

This article presents a new computational model for the generation of multimodal referring expressions (REs), based on observations in human communication. The algorithm is an extension of the graph-based algorithm proposed by Krahmer, van Erk, and Verleg (2003) and makes use of a so-called Flashlight Model for pointing. The Flashlight Model accounts for various types of pointing gestures of different precisions. Based on a notion of effort, the algorithm produces REs combining language and pointing gestures. The algorithm is evaluated using two production experiments with which spontaneous data is gathered on controlled input. The output of the algorithm coincides to a large extent with the utterances of the participants. However, an important difference is that the participants tend to produce overspecified REs, whereas the algorithm generates minimal ones. This article briefly discusses ways to generate overspecified multimodal references.
Users Browsing Behaviour in a DDC-Based Web Service: A Log Analysis

SUMMARY This study explores the navigation behaviour of all users of a large web service, Renardus, using web log analysis. Renardus provides integrated searching and browsing access to quality-controlled web resources from major individual subject gateway services. The main navigation feature is subject browsing through the Dewey Decimal Classification (DDC) based on mapping of classes of resources from the distributed gateways to the DDC structure. Among the more surprising results are the hugely dominant share of browsing activities, the good use of browsing support features like the graphical fish-eye overviews, rather long and varied navigation sequences, as well as extensive hierarchical directory-style browsing through the large DDC system.
The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy

Drawing on primary source material and interviews with statisticians and other scientists, "The Theory That Would Not Die" is the riveting account of how a seemingly simple theorem ignited one of the greatest scientific controversies of all time. Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years - at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information, even breaking Germany's Enigma code during World War II, and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA decoding to Homeland Security. "The Theory That Would Not Die" is a vivid account of the generations-long dispute over one of the greatest breakthroughs in the history of applied mathematics and statistics.
Evidence of validity of internal structure of the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-Sp-12) in Brazilian adolescents with chronic health conditions

This study explored the evidence of validity of internal structure of the 12-item Functional Assessment of Chronic Illness Therapy—Spiritual Wellbeing Scale (FACIT-Sp-12) in Brazilian adolescents with chronic health conditions. The study involved 301 Brazilian adolescents with cancer, type 1 diabetes mellitus, or cystic fibrosis. Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Item Response Theory (IRT) were used to test the internal structure. Reliability was determined with Cronbach’s Alpha and McDonald’s Omega. The EFA suggested a one-dimensional scale structure in contrast to the original 2-factor model or the 3-factor model which were not reproduced in the current CFA. All quality indicators for the EFA one-factor exceeded the required criteria (FDI = 0.97, EAP = 0.97, SR = 3.96 and EPTD = 0.96, latent GH = 0.90. and the observed GH = 0.85). The FACIT-Sp-12 for adolescents yielded strong evidence for a 1-factor model and with good reliability.
A cell-based assay for detection of anti-fibrillarin autoantibodies with performance equivalent to immunoprecipitation

Anti-fibrillarin autoantibodies are useful for the diagnosis and prognosis of systemic sclerosis (SSc). Anti-fibrillarin produces a clumpy nucleolar pattern in indirect immunofluorescence assay on HEp-2 cells (HEp-2 IFA). Here we develop and validate a reliable cell-based anti-fibrillarin assay (Fibrillarin/CBA) for use in clinical diagnostic laboratories. A TransMembrane Signal was fused to the human fibrillarin gene (TMS-fibrillarin). HEp-2 cells overexpressing transgenic TMS-fibrillarin at the cytoplasmic membrane were used as IFA substrate in the Fibrillarin/CBA. Sixty-two serum samples with nucleolar pattern in the HEp-2 IFA (41 clumpy; 21 homogeneous/punctate) were tested for anti-fibrillarin using Fibrillarin/CBA, immunoprecipitation (IP), line-blot and ELISA. In addition, samples from 106 SSc-patients were evaluated with Fibrillarin/CBA and the results were correlated with disease phenotypes. Thirty-eight of 41 samples with the clumpy nucleolar pattern (92.7%) were positive in the Fibrillarin/CBA, while all 21 samples with other nucleolar patterns were negative. Fibrillarin/CBA results agreed 100% with IP results. Among the 38 Fibrillarin/CBA-positive samples, only 15 (39.5%) and 11 (29%) were positive for anti-fibrillarin in line-blot and ELISA, respectively. Higher frequency of diffuse cutaneous SSc (dcSSc) phenotype (72.7% vs 36.8%; p=0.022), cardiac involvement (36.4% vs 6.5%; p=0.001) and scleroderma renal crisis (18.2% vs 3.3% p = 0.028) was observed in SSc patients with positive compared to negative Fibrillarin/CBA result. Performance of Fibrillarin/CBA in the detection of anti-fibrillarin autoantibodies was comparable to the gold standard IP. Positive Fibrillarin/CBA results correlated with disease phenotypes known to be associated with anti-fibrillarin autoantibodies, underscoring the clinical validation of this novel assay.
Content-based support for Persian learners of English

People learning a new language have problems with various aspects of the language they want to learn – with its grammar, with its pronunciation, with its morphology. CALL tools have been provided for most of these linguistic levels, but comparatively little has been done about helping students with problems of meaning. We will argue that language technology is now mature enough to support tools that address at least some semantic issues, and we will describe a tool that attempts to provide appropriate support for a specific class of learners.
Taguchi methods to improve the development process

A description is given of the Taguchi methods, which compromise combinations of engineering, statistics, economics, and information theory that greatly improve product development. Product parameter design optimizes the nominal values of design parameters to keep performance near complete customer satisfaction despite variances of parts and environment. Tolerance design selects the basic precision level that minimizes total cost. Process parameter design optimizes process parameters to maximise the intrinsic stability of production. Online quality control periodically checks and adjusts production to maintain operating precision that minimizes total cost. <<ETX>>