Miracle-dz/UniFAR-FTUs huggingface dataset:
AR-Tri-Training: Tri-Training with Assistant Strategy

The classification performance of the classifier is weakened because the noise samples are introduced for the use of unlabeled samples in Tri-training. In this paper a new Tri-training style algorithm named AR-Tri-training (Tri-training with assistant and rich strategy) is proposed. Firstly, the assistant learning strategy is posed. Then the supporting learner is designed by combining the assistant learning strategy with rich information strategy. The number of mislabeled samples produced in the iterations of three classifiers mutually labeling are reduced by use of the supporting learner, moreover the unlabeled samples and the misclassified samples of validation set can be fully used. The proposed algorithm is applied to voice recognition. The experimental results show that AR-Tri-training algorithm can compensate for the shortcomings of Tri-training algorithm, further improve the testing rate.
Theoretical and experimental biology in one—A symposium in honour of Professor Kuo-Chen Chou’s 50th anniversary and Professor Richard Giegé’s 40th anniversary of their scientific careers

It has been a dream that theoretical biology can be extensively applied in experimental biology to accelerate the understanding of the sophiscated movements in living organisms. A brave assay and an excellent example were represented by enzymology, in which the well-established physico-chemistry is used to describe, to fit, to predict and to improve enzyme reactions. Before the modern bioinformatics, the developments of the combination of theoretical biology and experimental biology have been mainly limited to various classic formulations. The systematic use of graphic rules by Prof. Kuo-Chen Chou and his co-workers has significantly facilitated to deal with complicated enzyme systems. With the recent fast progress of bioinformatics, prediction of protein structures and various protein attributes have been well established by Chou and co-workers, stimulating the experimental biology. For example, their recent method for predicting protein subcellular localization (one of the important attributes of proteins) has been extensively applied by scientific colleagues, yielding many new results with thousands of citations. The research by Prof. Chou is characterized by introducing novel physical concepts as well as powerful and elegant mathematical methods into important biomedical problems, a focus throughout his career, even when facing enormous difficulties. His efforts in 50 years have greatly helped us to realize the dream to make “theoretical and experimental biology in one”. Prof. Richard Giege is well known for his multi-disciplinary research combining physics, chemistry, enzymology and molecular biology. His major focus of study is on the identity of tRNAs and their interactions with aminoacyl-tRNA synthetases (aaRS), which are of critical importance to the fidelity of protein biosynthesis. He and his colleagues have carried out the first crystallization of a tRNA/aaRS complex, that between tRNAAsp and AspRS from yeast. The determination of the complex structure contributed significantly to under- stand the interaction of protein and RNA. From his fine research, they have also found other biological function of these small RNAs. He has developed in parallel appropriate methods for his research, of which the protein crystallogenesis, a name he has coined, is an excellent example. Now macromolecular crystallogenesis has become a developed science. In fact, such contribution has accelerated the development of protein crystallography, stimulating the study of macromolecular structure and function.
A Comparison Study of Several Adaptive Control Strategies for Resilient Flight Control

In this paper we decribe our initial development and testing of the framework referred to as Algorithm Design & Validation for Adaptive Nonlinear Control Enhancement (ADVANCE). The key elements of ADVANCE are suitable performance metrics for adaptive control systems, and an automated tuning procedure using our in-house developed Automatic Tuner for non-Linear and Adaptive Systems (ATLAS). The paper describes a comparison study of the state-of-the-art adaptive flight control algorithms on two challenging testbeds. The development of the ADVANCE framework involved several steps: (i) Development of suitable performance comparison metrics for adaptive control systems; (ii) Development of a “plug-and-play” capability that enables rapid implementation and simulation testing of different advanced adaptive control algorithms; and (iii) Comprehensive simulation studies and performance comparison of the state-of-the-art adaptive control algorithms on a high-fidelity simulation of miniature tail-sitter UAV with significant nonlinearities and uncertainty, and a semi-nonlinear simulation of F/A-18 dynamics. Results presented in the paper demonstrate the feasibility and potential of the ADVANCE framework, and further development of the algorithms and testing procedures is expected to give rise to a set of recommendations and guidelines regarding the use, tuning and implementation of different adaptive flight control algorithms to different problems in flight control. This will also facilitate flight certification of adaptive flight control algorithms.
Evaluating technology resistance and technology satisfaction on students' performance

Purpose – Using the extended task‐technology fit (TTF) model, this paper aims to examine technology resistance, technology satisfaction and internet usage on students' performance.Design/methodology/approach – The study was conducted at Universiti Teknologi MARA, Johor, Malaysia and questionnaires were distributed to 354 undergraduate students.Findings – The structural equation modelling (SEM) results indicate that technology satisfaction and the internet usage significantly explains the variance on students' performance. Task‐technology fit is not a predictor of technology resistance but it does predict the internet usage. The internet usage has greater impact on technology satisfaction than technology satisfaction on the internet usage. Finally, technology resistance is not a predictor of students' performance.Research limitations/implications – The study focuses only on education in Malaysia and concentrates only on the students' performance and the relationship between technology resistance, technolog.
Chaotic time series prediction using artificial neural networks

This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.
The Improved Collaborative Filtering Recommendation Algorithm Based on Cloud Model

The traditional collaborative filtering algorithm has a better recommendation quality and efficiency, it has been the most widely used in personalized recommendation system. Based on the traditional collaborative filtering algorithm,this paper considers the user interest diversity and combination of cloud model theory.it presents an improved cloud model based on collaborative filtering recommendation algorithm.The test results show that, the algorithm has better recommendation results than other kinds of traditional recommendation algorithm.
An Efficient Content-Based Retrieval System For 3D Objects

Abstract VRML is rapidly becoming the standard file format for delivering 3D content via the Internet. Most 2D and even 3D content-based retrieval techniques are designed based on 2-D information such as shape or texture comparisons. In this paper, we present a novel similarity method based on 3D information extracted from the VRML object database. Users may give a VRML object and find VRML scenes that use the similar object via our retrieval system. The system includes multiple subsystems, which are conducted in two main parts. The first part includes the VRML object parser system and the normalization system. The second part includes the comparison system, database management system, and a friendly graphical user interface, which improves the interaction and retrieval precision. Experience shows that the system can retrieve 3D objects from VRML databases with high satisfaction.
Predictors of Home Exercise Adherence in Older People with Osteoarthritis

Purpose: To identify factors associated with adherence to prescribed exercises in elderly, community-dwelling people with knee and/or hip osteoarthritis. Methods: Logistic regression was used to investigate associations among variables at the beginning of a home exercise program, after 4 weeks of performing exercises (test 2), and at the end of the 8-week program (test 3). Outcome measures were self-reported home exercise adherence at tests 2 and 3, and the predictors were exercise adherence behaviour in the clinic, concurrent physical activity, perception of being physically inactive, and correctness of exercise performance. Results: Home exercise adherence at test 2 was associated with “in-clinic” exercise adherence behaviour at test 2 (odds ratio [OR] = 1.48; 95% confidence interval [CI] = 1.09–2.01). There were significant associations between home exercise adherence at test 3 and (1) home exercise adherence at test 2 (OR = 19.86; 95% CI = 4.84–81.56); (2) concurrent physical activity at test 3 (OR = .
Inference Rules for XML Strong MVD and XML Weak MVD

For solving logical implication problem in the presence of XML strong multi-valued dependency(denoted as XSMVD) and XML weak multi-valued dependency(denoted as XWMVD) under incomplete information circumstances, the inference rules of XSMVD and XWMVD based on XML Schema were discussed. The concepts of XML Schema and incomplete XML document tree according with XML Schema were formalized. Based on the concepts of sub-tree information equivalence and sub-tree information consistent, the definitions of XSMVD and XWMVD were given and their nature was studied. When XSMVD and XWMVD exist at the same time in XML Schema, their inference rules were presented and their soundness was proved. The production in this work lays the foundation for normalization of XML Schema existing XSMVD and XWMVD at the same time under incomplete information circumstances.
Quantifying dose-dependent changes in visual flash-induced evoked response during halothane and isoflurane anesthesia

We investigated a dose-dependent modulation of flash-induced event-related potentials (ERP) and resting potentials (RP) recorded from rat primary visual cortex in waking and halothane- and isoflurane-anesthetized rats. Our results show that slow oscillations in flash-induced afterdischarge (FAD) range of frequencies and gamma (20-60 Hz) oscillations are present at rest during waking and light-to-moderate anesthetized states. While the temporal occurrence of these oscillations appears random during rest, FAD and gamma oscillations appear entrained following flash stimulation. During gradual increase in anesthetic dose, FAD is gradually suppressed between 0.1% and 0.4% of both halothane and isoflurane. However, FAD suppression is consistently stronger for isoflurane than for halothane. On the other hand, gamma oscillations are gradually enhanced between 0.1% and 1.5% of both halothane and isoflurane. This enhancement is consistently stronger for isoflurane than halothane. At the anesthetic dose of 1.5%, gamma power is abolished with halothane but is still present with isoflurane. Since gamma power is enhanced at anesthetic doses at which consciousness is lost (0.4-0.8%), our results support the view that reduction in gamma power is not correlated with the loss of consciousness.
Continuous-time model identification from sampled data: Implementation issues and performance evaluation

This paper deals with equation error methods that fit continuous-time transfer function models to discrete-time data recently included in the CONTSID (CONtinuous-Time System IDentification) Matlab toolbox. An overview of the methods is first given where implementation issues are highlighted. The performances of the methods are then evaluated on simulated examples by Monte Carlo simulations. The experiments have been carried out to study the sensitivity of each approach to the design parameters, sampling period, signal-to-noise ratio, noise power spectral density and type of input signal. The effectiveness of the CONTSID toolbox techniques is also briefly compared with indirect methods in which discrete-time models are first estimated and then transformed into continuous-time models. The paper does not consider iterative or recursive algorithms for continuous-time transfer function model identification.
A communication scheme for analog VLSI perceptive systems

A communication architecture tailored for analog VLSI perceptive systems is proposed. Information is generated on a transmitter array of cells each driving a pulse generator. The resulting pulse-frequency modulated signals are transmitted through the nonarbitered, asynchronous access of pulses to a common bus. Pulses are decoded and accumulated in a receiver chip and the mapping of the activity distribution of the transmitter onto the receiver is achieved. One possible implementation of these principles is presented. The circuit description of all blocks is given and experimental results are shown: they satisfactorily support the theoretical basis upon which the system was constructed. Extensions to the communication architecture are finally presented. >
The Content Analysis of Media Frames: Toward Improving Reliability and Validity

The main purpose of this study was to shed light on methodological problems in the content analysis of media frames. After a review of 5 common methods, we will present an alternative procedure that aims at improving reliability and validity. Based on the definition of frames advanced by R. M. Entman (1993), we propose that previously defined frame elements systematically group together in a specific way. This pattern of frame elements can be identified across several texts by means of cluster analysis. The proposed method is demonstrated with data on the coverage of the issue of biotechnology in The New York Times. It is concluded that the proposed method yields better results in terms of reliability and validity compared to previous methods.
Mobile propagation loss with a low base station antenna for NLOS street microcells in urban area

Path loss for non-line-of-sight (NLOS) propagation in urban streets with a low base station antenna is simulated. Typical path loss curves are shown to be characterized by three,slopes and two break points. The path loss exponents for each part at different frequency are calculated. The frequency and the road width's effects on path loss are discussed. An explanation for the results is also included in this paper.
Heuristics - Based Stereo Matching

This paper presents an improved stereo matching algorithm by heuristic strategy technique resulting from that the stereo matching problem can be cast as a search one. After early processing, our algorithm employs two search ways. One is intra-scanline search and the other a inter-scanline search. Both of them a can be calculated separately and treated as the problem of finding an optimal path on 2-D search graph by graph searching method with the concentration on minimizing some combination of cost of the path and effor of the search required to get the path, that is heuristic. Our algorithm hs been tested with block scences and its computational requirements have been discussed too.
Sensor technology integration in an intelligent machine for herring roe grading

The development and integration of sensor technology for herring roe grading is described. In this application, by and large, grading is presently done by hand. Shape, firmness/texture, color and weight all play key roles in determining the grade of a roe skein. Furthermore, number of these variables are quite subjective both in the way they are determined by human graders, and in the way they affect the overall grade of a skein. Thus, in the present system an "intelligent" decision-making system, with multiple levels of abstraction, is used to determine the final grade of the product. The system uses a model base and also a knowledge base developed through interactive acquisition of knowledge from grading experts and off-line experiments. These are implemented as a set of fuzzy-logic rules and model matching procedures. A prototype grading machine has been developed and tested at an industrial plant. Typical experimental results are presented and studied.
Non conventional signal processing by the use of sigma delta technique: a tutorial introduction

The one-bit high-speed data stream generated by sigma-delta modulators can be transformed into a high-resolution analog or digital signal since the spur affecting the one-bit stream is concentrated at high frequency. It is shown that the same feature also gives interesting advantages in efficient signal processing. The double nature, both analog and digital, of a sigma-delta bit stream allows mixed nonconventional processing functions, including nonlinear operations. The advantages in terms of circuit complexity and integrated implementation of silicon area are very promising. In this tutorial introduction to the method, how to perform basic processing functions using sigma-delta bit streams is described. <<ETX>>
Tetra-n-butylammonium iodide: a space-group revision

The crystal structure of tetra-n-butyl­ammonium iodide, C16H36N+·I−, has been redetermined at room temperature and at 100 (1) K. In the low-quality (R = 0.142) room-temperature determination by Wang, Habenschuss, Xenopoulos & Wunderlich [Mol. Cryst. Liq. Cryst. Sci. Technol. Sect. A (1995), 264, 115–129], this structure was described as crystallizing in the space group C2 with Z′ = 2. Our results prove that the correct space group is C2/c (with the same unit-cell parameters as in the original determination) at both temperatures. In the crystal structure, the iodide anions fill the voids in the grid-like cationic structure. Weak C—H⋯I inter­actions (eight per anion) strengthen this packing.
Technologies in Computerized Lexicography

Since the early eighties, computer technology has become increasingly relevant to lexicography. Computer science will probably not be the only technological discipline which may have implications for future computerized lexicography. Some developments in the fields of lan­ guage technology, information technology and knowledge engineering, may support lexico­ graphical practice and enhance the quality of the resulting dictionary. The present paper discusses how the analysis and interpretation of electronic corpus data by the lexicographer may be improved by automatic linguistic analYSiS, by better access to the corpus, and by a more flexible communication with the computer system. As a frame of reference, first an indication of the state of the art in computerized leXicography will be given, by a concise discussion of three projects at the Institute for Dutch Lexicology INL considered in an international context: the conversion of the Woordenboek der Nederlalldsche Taal WNT (Dictionary of the Dutch Language Based on Historical Principles) to electronic form, the compilation of the Vroegmiddelllederlands Woordellboek (Dictionary of Early Middle Dutch) in a computerized lexicographer's workbench, and the INL Taalbank (INL Language Database). Although the topic of this paper is technology, focus is on functional rather than technical aspects of compu terized lexicography.
Study on a New Joint Source-Channel Decoder Design

To improve upon the Low-Density Parity-Check (LDPC) codes , incorporating compressed sensing (CS) and information redundancy, a new joint decoding algorithm frame is presented. The proposed system exploits the information redundancy by CS reconstruction during the iterative decoding process to correct decoding of LDPC codes. The simulation results show that the algorithm presented can improve system decoding performance and obviously make bit error ratio (BER) lower then traditional LDPC codes. In addition, a relatively short argument is given on different CS reconstructed algorithms in proposed system, the new design is shown to benefit from different CS reconstructed algorithms.
Tagged Web Image Retrieval Re-ranking with Wikipedia-based Semantic Relatedness

Now a days, to make good use of tags is a general tendency when users need to upload or search some multimedia data such as images and videos on the Web. In this paper, we introduce an approach to calculate semantic importance of tags and to make re-ranking with them on tagged Web image retrieval. Generally, most photo images stored on the Web have lots of tags added with user`s subjective judgements not by the importance of them. So they become the cause of precision rate decrease with simple matching of tags to a given query. Therefore, if we can select semantically important tags and employ them on the image search, the retrieval result would be enhanced. In this paper, we propose a method to make image retrieval re-ranking with the key tags which share more semantic information with a query or other tags based on Wikipedia-based semantic relatedness. With the semantic relatedness calculated by using huge on-line encyclopedia, Wikipedia, we found the superiority of our method in precision and recall rate as experimental results.
Comparison controllers for inverter operating in island mode in microgrids with linear and nonlinear loads

This paper presents the design and implementation of a resonant controller into a PI-P control configuration (PI-P+Resonant controller). The design of this controller is conducted for inverter operation in island mode within the context of microgrids The main PI-P control is avoid that large control signal causing the saturation phenomena in the systems. The Resonant controller allows providing high gain at the frecuency of the harmonics, in order to mitigate these harmonics. If both controller are combiate (PI-P-Resonant controllers) turns out to be an adequate solution to reduce total armonic distortion in the output voltage (THDv) of a single-phase inverter due to nonlinear loads.
Frontostriatal Cognitive Staging in Parkinson's Disease

Cognitive impairment and behavioural disorders are often encountered in subjects with Parkinson's disease (PD). A simple PD-related frontostriatal cognitive dysfunction (PDFCD) staging is proposed. Executive dysfunction and mental fatigue (stage I), depression/anxiety (stage IIa), apathy/pain (stage IIb), and dementia (stage III) reflect a sequential process of dopamine depletion occurring in different regions of the striatum (stages I and II) and the frontal cortex (stage III). In addition to these nonmotor manifestations present in the unmedicated (OFF) state, the PDFCD model also predicts a number of complications related to dopaminergic treatment (ON state), from impulse control disorders (stages I and IIa) to hallucinations (stage IIb) and psychosis (stage III). Although the model admittedly needs further refinements, it provides a framework for hypothesis testing and may help clinicians optimize therapeutic strategies.