Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Learning Styles, Stages of Self­ Direction in Learning and Academic Performance in a Case­ Based Nursing Program

and concrete modes might be due to the composition of the population sampled. In the research establishing concrete experience as the preferred mode of learning (Laschinger, 1986), the students sampled were third-year students . Haislett et al (1993) assumed that these students had experienced at least some of the applied curricu la of the nursing program, and had completed the more theory-based science course work and general university requirements typical of the first semester of a nursing program. Thus , their third year learning style cou ld be influenced not only by their naturally occurring preference for concrete experience, but also by the lack of demand for the strategies required to master course work more compatible with abstract conceptua lization and reflect ive observation. Compared to Laschinger (1986), the sample selected in Haislett et al (1993) study came from a population restricted to first year nursing students
Compiler Optimization of Array Data Storage

The literature has witnessed much work aimed at improving the efficiency of mernory systems. The motivation is obvious: the high cost of page faults in hierarchical stores. Most architectures, including vector processors, shared - and distributed - memory multiprocessors, and interleaved memories, similarly reward data locality and predictable patterns of access. Most current endeavors, however, prefix the storage organization of data operands and either manipulate loops in the code, tailor algorithms, or tune prefetching strategies and replacement policies. A methodology and an algorithm for automatically organizing the storage of array data for efficient access by the executing code are described. The simple techniques presented may be incorporated in a compiler and are complementary to the other optimizations in the literature. Furthermore, examples in Fortran 8X and Fortran 77 pseudo-code support the general applicability of the work to programming languages, both scalar as well as array. Notwithstanding the column-major storage constraints, a technique for optiimizing storage in Fortran 77 is outlined. The prudence of of a compiler-optimized approach over a user-optimized approach to data storage organization is discussed.
METODE PENAPISAN CABAI (CAPSICUM ANNUUM L.) UNTUK KETAHANAN TERHADAP CHILLI VEINAL MOTTLE VIRUS (Chi VMV) DAN CUCUMBER MOSAIC VIRUS (CMV)

Screening Method for Chilli Veinal Mottle Virus (Chi VMV) and Cucumber Mosaic Virus (CMV) Resistance in Chillipepper. ChiVMV and CMV have been reported as the causal agents of main diseases in chillipepper in Indonesia and other Asian countries. Mix infection of this two viruses was commonly occurred in the field, causing severe disease . The use of resistance varieties has been proposed for dealing with the yield losses causing by the viruses. Breeding program is undergoing for development of chillipepper varieties resistant to ChiVMV and CMV. Methodology for routine screening activity of chillipepper for resistance to both ChiVMV and CMV needs to be established. This research was conducted in Cikabayan Glass House and Plant Virology Laboratory, Plant Protection Department, Bogor Agricultural University from May 2006 to June 2007. Aim of the research was to develop screening method for simultaneous infection by the two viruses, ChiVMV and CMV. Inoculation of ChiVMV and CMV was done by single inoculation or repetitive inoculation methods. In both methods, ChiVMV and CMV were inoculated in different sequences, either ChiVMV or CMV first. The result showed that incubation period was shorter when CMV was inoculated in advance both in single and repetitive inoculation method. Mosaic, mottle and malformation type symptom was observed in infected plants. Based on disease incidence, infection of ChiVMV was higher compared to CMV in repetitive inoculation as well as in single inoculation. Repetitive inoculation methods with virus sequence ChiVMV-CMV-ChiVMV-CMV was selected for resistance evaluation of chillipepper genotypes.
Automatic Recognition of Dialogue Acts

This thesis deals with automatic Dialogue Act (DA) recognition in Czech and in French. Dialogue acts are sentence-level labels that represent different states of a dialogue, such as questions, statements, hesitations, etc. The first main contribution of this work is to propose and compare several approaches that recognize dialogue acts based on three types of information: lexical, prosodic and word positions. These approaches are tested on the Czech Railways corpus that contains human-human dialogues, which are transcribed both manually and with an automatic speech recognizer for comparison. The experimental results confirmed that every type of feature (lexical, prosodic and word positions) bring relevant and somewhat complementary information. The proposed methods that take into account word positions are especially interesting, as they bring global information about the structure of a sentence, at the opposite of traditional n-gram models that only capture local cues. One of the main issue in the domain of automatic dialogue act recognition concerns the design of a fast and cheap method to label new corpora. The next main contribution is to apply the general semi-supervised training approach based on the Expectation Maximization algorithm to the task of labeling a new corpus with the pre-defined DAs. We further proposed to filter out the examples that might be incorrect by two confidence measures, namely the maximum a posteriori probability and the a posteriori probability difference methods. Experimental results showed that the proposed method is an efficient approach to create new dialogue act corpora at low costs.
Performance of EM-based multiuser detection for space-time block coded WCDMA systems over multipath fading channels

We present a multiuser detection (MUD) scheme derived from the expectation maximization (EM) algorithm for the downlink of space-time block coded (STBC) WCDMA systems. We consider the downlink scenario with two transmit antennas and a single receive antenna and multipath fading channels. The EM-based MUD looks iteratively for the maximum-likelihood solution. Its structure is very similar to the parallel interference cancellation (PIC) receiver but with better convergence properties. Our simulation results show significant performance gains over conventional and PIC receivers.
A Survey on Sentiment Analysis Data sets and Techniques

This survey reviews the recent progress in the field of sentiment analysis with the focus on available datasets and sentiment analysis techniques. Since many exhaustive surveys on sentiment analysis of text input are available, this survey briefly summarizes text analysis techniques and focuses on the analysis of audio, video and multimodal input. This survey also discuses different available datasets. In most of the work datasets are prepared as per specific research requirements. This survey also discusses methods used to prepare such datasets. This survey gives an overview of available datasets, methods to prepare data sets, sentiment analysis techniques, and challenges in this area. Key wordsSentiment Analysis, Opinion Mining, Multimodal Sentiment Analysis, datasets, sentiment analysis
Primary cutaneous rhinosporidiosis

Primary cutaneous rhinosporidiosis is very rare and only 10 cases have been reported in India. A 51 year old man had a painless, progressive ulcer for 6 months on the right leg. The ulcer was 2 cm x 2 cm and, had raised, irregular, nodular and partly, undermined margins. Biopsy of the ulcer margin revealed rhinosporidiosis. Excision led to uneventful healing.
A computationally feasible test day model with separate first and later lactation genetic effects

In a two step analysis test day effects were estimated within herd with adjustment for across herd effects and then the adjuste d data were analysed across herd. Genetic effects were defined for each of 10 months in milk within first and later lactation an d for milk, fat and protein giving 60 traits. The rank of the genetic (co)variance matrix ( G) was reduced to 6 such that G retained the information to evaluate the selection objective. A repeatability model allowed for multiple lactations with each lactation, conceptually, e xpressing all 60 traits, but missing observations for 30 or more. A canonical transformation was applied to create uncorrelated traits. Missing values were replaced by their expectations at each round. Because of the rank reduction, only 6 canonical traits were solved f or. This system should make evaluations more stable by removing biases due to genetic differences in persistency and rate of maturity.
Dynamic Decision Making for Humanoid Robots Based on a Modular Task Structure

Within the last years a new challenging field of robotics has arisen in which assisting robots cooperate and interact with humans, both imitating their behaviour patterns and performing with them and/or in their environment diverse complex tasks. Due to the ambitious tasks and the complexity of a time varying environment, these ''humanoid'' robots have to be provided with much more intelligence in comparison with the current industrial robots available on the market. Thus, the robot has to dispose on the one hand of a large variety of dedicated sensors which cover the full range of human perception modalities and which collect information about the state of the robot and of the environment. On the other hand the control concept has to provide the capability of extracting, combining and analyzing this information in order to cope autonomously with these extreme conditions in the most appropriate way. Moreover, in order to be able to face a manifold of different possible situations, the robot has to manage specific human-like skills. That means it has to perceive, act, deliberate and communicate in a robust manner.
Reinforcement Learning Algorithm for Solving Load Commitment Problem Considering a General Load Model

Under the smart grid paradigm, in the near future all consumers will be exposed to variable pricing schemes introduced by utilities. Hence, there is a need to develop algorithms which could be used by the consumers to schedule their loads. In this paper, load scheduling problem is formulated as a LCP (load commitment problem). The load model is general and can model atomic and non-atomic loads. Furthermore, it can also take into consideration the relative discomfort caused by delay in scheduling any load. For this purpose, a single parameter “udc” is introduced in the load model which captures the relative discomfort caused by delay in scheduling a particular load. Guidelines for choosing this parameter are given. All the other parameters of the proposed load model can be easily specified by the consumer. The paper shows that the general LCP can be viewed as multi-stage decision making problem or a MDP (Markov decision problem). RL (reinforcement learning) based algorithm is developed to solve this problem. The efficacy of the algorithm is investigated when the price of electricity is available in advance as well as for the case when it is random. The scalability of the approach is also investigated.
Live Broadcasting Online: Interactive Training for Rural Special Educators

This paper describes how to use a desktop computer and inexpensive software plus a PC or Macintosh streaming server to deliver live interactive class sessions via video with audio streaming on the Internet. Although the use of Web-based instruction for preservice and inservice program delivery in special education and disability services is expanding rapidly, most existing programs rely primarily on text presentation and asynchronous (delayed time) technologies such as threaded discussions. Relatively little use has been made to date of the Web's multimedia capabilities or synchronous (real time) technologies such as audio- or video-conferencing. The use of webcasting technology (both simulcasts in real time and re-broadcasts on demand) represents a fairly inexpensive, simple to use mechanism for delivering personnel preparation programs for practitioners working in early intervention, special education, or adult disability services in rural areas without the need for high bandwidth connections. The distance education program in Severe/Multiple Disabilities and Early Intervention Special Education at West Virginia University has successfully utilized webcasting technology to deliver a graduate certification and degree program to practicing but uncertified special educators working in rural areas of the United States as well as in several other locations around the world.
Wavelet analysis of the gut myoelectrical activity relationship with mechanical activity

The electroenterogram (EEnG) is the myoelectrical signal of the smooth muscle of the small bowel. This signal can be recorded through bipolar electrodes placed in the intestinal serosa. The objective of this study, is to determinate the relationship that exists between the electroenterogram and the pressure signal. Were taken 14 sessions of record of the myoelectrical signal. The pressure signal was recorded using a latex microballoon, implanted through surgery, in the same ring of the layer of circular muscle, in which the bipolar electrode was implanted. The signals were amplified and acquired simultaneously. The continuous wavelet transform was calculated (in its discrete model), using the Morlet's wavelet. Eleven scales of frequency were chosen for the wavelet transform. The energy of the levels of frequency /spl nu//sub 2/-/spl nu//sub 10/ and the energy of the pressure signal reached high correlation coefficients (around 0.8). The greater means correlation coefficient (0.83) was obtained by levels /spl nu//sub 8/-/spl nu//sub 9/. Those levels correspond to the band of frequency 12.064-20.769 Hz. The levels /spl nu//sub 8/-/spl nu//sub 9/ contain the high frequency components, which correspond to spike burst. There aren't significant differences among levels of frequency /spl nu//sub 2/-/spl nu//sub 10/. Therefore, the energy frequency levels /spl nu//sub 2/-/spl nu//sub 10/ can be used to represent intestinal motility indexes (IMIs).
Assessment of musculoskeletal stress marker development in the hand

The analysis of musculoskeletal stress marker (MSM) development is a commonly employed tool in osteological surveys and is used to infer patterns of occupational activity and societal organisation in archaeological populations. Although the majority of research into upper limb MSMs has focused on the bones of the arm, the bones of the hand have been conspicuous by their absence. This is likely to be due to methodological issues surrounding the study of hand bones and a presumed lack of variation in MSM development in this area. To date, there have been no systematic studies investigating the presence and variation in MSM morphology for the muscles of the human hand. To address this issue, a presence/absence scoring system was developed for twelve sites of muscle origin and insertion in the metacarpals and phalanges, which was used to determine bilateral asymmetry in the hands of 31 individuals from the Naval Hospital Cemetery site in Greenwich, London. Analysis found observable variation in MSM development between and within the hands, which could be used to determine patterns of asymmetry within the sample. Comparisons with MSM scores from the humeri of these individuals indicate a differentiation in MSM development and asymmetry between these anatomical regions. Levels of asymmetry in the hands and humeri were generally low, with only the dorsal interossei displaying statistically significant asymmetry. Subsequent upper limb MSM research will benefit from the inclusion of data from the hands. These results do not support the continued use of the humerus as a proxy for MSM expression across the upper limb as a whole and suggest that important information regarding behavioural asymmetry in the hands is being lost because of the continual exclusion of this anatomical unit from MSM research.
Model selection and randomization for weakly dependent time series forecasting

Observing a stationary time series, we propose in this paper new two steps procedures for predicting the next value of the time series. Following machine learning theory paradigm, the first step consists in determining randomized estimators, or "experts", in (possibly numerous) different predictive models. In the second step estimators are obtained by model selection or randomization associated with exponential weights of these experts. We prove Oracle inequalities for both estimators and provide some applications for linear, artificial Neural Networks and additive non-parametric predictors.
A comparative study of Roth-Erev and modified Roth-Erev reinforcement learning algorithms for uniform-price double auctions

This work focuses on multi-agent learning in market contexts. It reports findings from a comparative study of three reinforcement learning algorithms currently in use for a variety of market applications. Two double-auction market testbeds are developed and used to carry out benchmark comparisons involving intensive parameter sweeps with heat map visualization of parameter sensitivities. A primary concern is the degree to which each tested algorithm permits learning agents to converge to the choice of a best action measured in terms of accumulated profits. Some findings from a mathematical analysis of the algorithms’ properties are also reported. The three reinforcement learning algorithms studied in this work are: the Roth-Erev algorithm proposed by Erev and Roth [1], the Modified Roth-Erev (MRE) reinforcement learning algorithm proposed by Nicolaisen et al [2] and the Variant Roth-Erev (VRE) learning algorithm proposed by Sun and Tesfatsion [3].
The role of microglia in amyotrophic lateral sclerosis: Analysis of microRNAs

Amyotrophic lateral sclerosis (ALS) is a progressive adult onset neurodegenerative disease characterized by selective death of the upper and lower motor neurons of the brain and spinal cord. Neuromuscular synapses are lost leading to paralysis and ultimately death. Nonneuronal cells, such as astrocytes, oligodendrocytes, and microglia, have been shown to contribute to ALS disease progression in mouse models. Microglia, the innate immune cells of the central nervous system, have been shown to be activated in ALS and contribute to disease progression. Hundreds of mRNAs have shown to be dysregulated in a variety of ALS cell types and tissues, including total spinal cord, acutely isolated microglia, and in vitro differentiated motor neurons. These mRNAs can be regulated post-transcriptionally by microRNAs (miRNAs), which are small endogenous non-coding RNAs with important regulatory roles in a wide range of cellular processes. This dissertation examines the contribution of miRNAs to ALS disease progression in microglia. I acutely isolated primary microglia from the spinal cords of transgenic mice overexpressing human wild type (WT) SOD1 and human G93A SOD1. I used small RNA sequencing to profile the miRNAs that are expressed during disease progression, and identified miRNAs that are differentially expressed. I confirmed these results by quantitative PCR and examined the expression changes of predicted targets in a microglia RNA-seq dataset. Here I show that miRNAs are dysregulated in acutely isolated microglia from SOD1 G93A transgenic
A reduced MIMO Wiener model for recursive identification of the depth of anesthesia

This paper presents a modeling and identification strategy for the depth of anesthesia using the propofol and remifentanil rates as the system inputs, and the bispectral index and state entropy measurements as the systems outputs. The standard model used for this purpose has twenty two patient‐dependent parameters. This high number of parameters, the little input excitation, and the small amount of output data make classical system identification approaches unsuccessful. To overcome these issues, the new model presented in this paper has six parameters, thereby meeting the parsimony principle of system identification. An extended Kalman filter algorithm is also developed and applied to real data. The good fitting results, combined with noise suppression and a recursive update of the model parameters, are promising for the design of the depth of anesthesia controllers to be used in real time platforms. Copyright © 2013 John Wiley & Sons, Ltd.
N-Hydroxylation of 2-Acetylaminofluorene in the Rabbit

Summary The major urinary metabolites of 2-acetylaminofluorene (AAF) in the rabbit were N-hydroxy-2-acetylaminofluorene and 7-hydroxy-2-acetylaminofluorene. By the third day of AAF feeding (70 mg AAF/day), N-hydroxy-2-acetylaminofluorene was the predominant urinary metabolite, and its excretion accounted for 22–30 per cent of the daily dose of ingested AAF during the first 4 weeks of feeding. During this same time interval, 12–28 per cent of the dose of AAF per day was excreted as 7-hydroxy-2-acetylaminofluorene. Only small (0.5–1.5 per cent of dose) or trace (0.1–0.5 per cent of dose) amounts of 3-hydroxy-2-acetylaminofluorene and 5-hydroxy-2-acetylaminofluorene were excreted. The rabbits did not excrete detectable quantities (more than 0.1 per cent of dose) of 1-hydroxy-2-acetylaminofluorene. N-Hydroxy-2-acetylaminofluorene was excreted entirely as a conjugate which was hydrolyzed by bacterial β-glucuronidase. 7-Hydroxy-2-acetylaminofluorene was excreted mainly as a conjugate cleaved by β-glucuronidase; in addition, however, small amounts of the unconjugated form or the ethereal sulfate were excreted.
Quality of service control for rt-VBR connections in ATM networks

Nowadays, networks must support applications such as distance learning, electronic commerce, access to the Internet, intranets and extranets, voice over IP (Internet Protocol) and many others. These new applications, employing data, voice, and video traffic, require high bandwidth and quality of service (QoS). The ATM (asynchronous transfer mode) technology, together with dynamic resource allocation methods, offers network connections that guarantee QoS parameters, such as minimum losses and delays. This paper presents a system that uses network management functions together with dynamic resource allocation for provision of end-to-end QoS parameters for rt-VBR (real-time variable bit rate) connections.
UER technique: conceptualisation for agent oriented development

The problem of conceptualisation is the first step towards the identication of the functional requirements of a system. This article proposes two extensions of well-known object oriented techniques: UER (User-Environment-Responsibility) technique and enhanced CRC (Class-ResponsibilityCollaboration) cards. UER technique consists of (a) looking for the users of systems and describing the ways the system is used; (b) looking for the objects of the environment and describing the possible interactions; and (c) looking for the general requirements or goals of the system, the actions that it should carry out without explicit interaction. The enhanced CRC cards together with the internal use cases technique is used for dening collaborations between agents. These techniques can be easily integrated in UML (Unied Modelling Language) [2], dening the new notation symbols as stereotypes.
Review of sensorless methods for brushless DC

This paper provides a review of the literature addressing sensorless operation of brushless DC machines. Methods explained are state-of-the-art, including those using: (1) measured currents, voltages, fundamental machine equations and algebraic manipulations; (2) observers; (3) the back-EMF method; (4) sensorless starting techniques; and (5) novel techniques not in the previous categories.