Miracle-dz/UniFAR-FTUs huggingface dataset:
Small Internal Antenna Using Multiband, Wideband, and High‐Isolation MIMO Techniques

In this paper, a small internal antenna for a mobile handset is presented using multiband, wideband, and high‐isolation multiple‐input multiple‐output techniques. The proposed antenna consists of three planar inverted‐F antennas (PIFAs) that operate in the global system for mobile communication (GSM900), the digital communication system (DCS), the personal communication system (PCS), the universal mobile telecommunication system (UMTS), and wireless local area network (WLAN) bands with a physical size of 40 mm × 10 mm × 10 mm. A resonator attached to the folded PIFA creates dual resonances, achieving a wide bandwidth of approximately 460 MHz, covering the DCS, PCS, and UMTS bands; a meander shorting line is used to improve impedance matching. Additionally, a modified neutralization link is embedded between diversity antennas to enhance isolation, which results in a 6‐dB improvement in the isolation and less than 0.1 in the envelope correlation coefficient evaluated from the far‐field radiation patterns. Simulation and measurements demonstrate very similar results for S‐parameters and radiation patterns. Peak gains show 3.73 dBi, 3.77 dBi, 3.28 dBi, 2.15 dBi, and 5.86 dBi, and antenna efficiencies show 56.15%, 72.15%, 68.59%, 52.92%, and 82.93% for GSM900, DCS, PCS, UMTS, and WLAN bands, respectively.
Abordagem não supervisionada para extração de conceitos a partir de textos

This paper presents an investigation about concepts extraction from texts using clustering algorithms. We applied a hybrid approach to select feature candidates and the CLUTO tool to support the process of clustering of terms. The analysis of identified concepts was manual. The details and preliminaries results of this approach for portuguese texts are discussed.
Aryloxy Phosphoramidate Triesters: a Technology for Delivering Monophosphorylated Nucleosides and Sugars into Cells

Prodrug technologies aimed at delivering nucleoside monophosphates into cells (protides) have proved to be effective in improving the therapeutic potential of antiviral and anticancer nucleosides. In these cases, the nucleoside monophosphates are delivered into the cell, where they may then be further converted (phosphorylated) to their active species. Herein, we describe one of these technologies developed in our laboratories, known as the phosphoramidate protide method. In this approach, the charges of the phosphate group are fully masked to provide efficient passive cell‐membrane penetration. Upon entering the cell, the masking groups are enzymatically cleaved to release the phosphorylated biomolecule. The application of this technology to various therapeutic nucleosides has resulted in improved antiviral and anticancer activities, and in some cases it has transformed inactive nucleosides to active ones. Additionally, the phosphoramidate technology has also been applied to numerous antiviral nucleoside phosphonates, and has resulted in at least three phosphoramidate‐based nucleotides progressing to clinical investigations. Furthermore, the phosphoramidate technology has been recently applied to sugars (mainly glucosamine) in order to improve their therapeutic potential. The development of the phosphoramidate technology, mechanism of action and the application of the technology to various monophosphorylated nucleosides and sugars will be reviewed.
Classification‐Based Approach for Hybridizing Statistical and Rule‐Based Machine Translation

In this paper, we propose a classification‐based approach for hybridizing statistical machine translation and rule‐based machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto‐evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut‐off method. In our experiments, using the aforementioned cut‐off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% — a 5.0% improvement over existing methods.
A Novel Decoupled LOS Rate Estimator for Terminal Guidance

An novel decoupled estimation algorithm based on kalman filter is presented to solve the line-of-sight (LOS) rate estimation problem in terminal guidance of air-to-air combat. The measurements of target azimuth and elevation are obtained by missile-borne active radar seeker which use a monopulse doppler radar. As it cant be directly measured by this kind of radar, the LOS rate which is needed as the input of guidance law should be estimated from these angle measurements. The close-loop simulation of LOS rate estimation in typical terminal guidance scenario that an air-to-air missile seeks a military fighter validates the presented algorithm.
Computer-simulation gaming systems utilizing neural networks and genetic algorithms

In recent years, neural networks and genetic algorithms (GAs) have been studied quite extensively by many researchers. They have been applied to various actual problems. In this paper, neural networks and GAs are applied to the computer gaming system which is the modified version of the COMMONS GAME. It is shown that neural network technology is quite helpful for making a copy of each player's strategy in game playing. It is also shown that GAs can be utilized for making the game playing exciting. Further, applications of neural networks and GAs to the familiar computer simulation games `Nobunaga's Ambition' and `Sangokushi' are briefly introduced in the final part of this paper.
Macrozooplankton Image Edge Detection Using Wavelet Packet Decomposition

Comparing with the phytoplankton, there are few researches on zooplanktons. Now, many waterworks don’t monitor the zooplanktons in source water. There isn’t effective detection method for several common macro zooplanktons such as chironomid larvae, cyclops and so on, and little has been done in the field of the macro zooplanktons automatic identification and monitor. This paper puts for forward a macrozooplankton edge detection method based on wavelet packet decomposition and reconstruction. We erase the high frequency parts by applying wavelet packet decomposition in the original images and then detect the edge of reconstruction images using the common edge detectors such as Prewitt, Sobel, Roberts, Laplacian of Gaussion, Canny and so on. The experimental results show that the edge detection methods in the reconstruction image work better than in the original image.
Evolutionary routing method for multi mobile robots in transportation

Recently, evolutionary calculation has been widely used in design problems. Using this method, intelligent control is expected to be constructed adaptable to disturbances. In this paper, a routing algorithm for multi mobile robots in transportation is presented. This algorithm is based on the Ant System and extended to the routing of multi mobile robots in transportation. The proposed algorithm is applied to two kinds of transportation problems, multi vehicle transportation and routing for multi Auto Guided Vehicles (AGV) in a semiconductor fabrication bay.
A 64 b microprocessor with multimedia support

A quad-issue microprocessor chip implements a 64 b architecture extension to a popular 32 b RISC instruction set. Additional instructions and dedicated hardware provide up to 10/spl times/ speed-up of image processing and rendering algorithms, including video compression/decompression and texture-mapped 3D triangles. The chip contains 5.2M transistors on a 17.7/spl times/17.8 mm/sup 2/ die in 0.5 /spl mu/m CMOS with 4 metal layers. The package is a 620-pin plastic BGA with 187 power and ground pins. Operating at 167 MHz, it dissipates less than 30 W from a 3.3 V supply.
CURRENT APPROACHES TO RESEARCHING SECOND LANGUAGE LEARNER PROCESSES

Language learning is a complex set of processes that largely take place in the learner's head. The extent to which learners consciously focus on specific aspects of language, the degree to which they notice particular features of language, and how this is done has been the object of considerable debate in different theoretical approaches to second language acquisition. For researchers in second language acquisition, one dilemma is how to find out what learners notice, and how, if at all, they incorporate this into their developing linguistic knowledge. Here, I discuss three approaches to researching learner cognitive processes that can be used to identify the knowledge that learners have about their second language, and obtain some insights into the cognitive processes of learners. These approaches have the potential to contribute to our understanding of how learners learn a second language, and, therefore, how this task may be facilitated. The first approach attempts to tap directly into the learner's thought through the use of think-aloud protocols, whereas the second involves having learners engage with activities that encourage them to talk aloud, thus providing insights into their thought processes. The third approach uses planning effects on task performance to investigate how learners monitor their language.
Enhancements for RTT-Fair HighSpeed TCP

TCP is known to have bandwidth fairness problems for flows of different RTT. HighSpeed TCP, which adapts TCP's congestion avoidance to grow faster, and thus be able to scale to high bandwidth environments, aggravates the RTT fairness problem since the congestion window increases at a rate proportional to the RTT and the current window size. We propose a method to eliminate the RTT fairness problem for competing high bandwidth flows. We decouple the rate of window growth in HighSpeed TCP from the current window size, such that competing flows adjust their window size, instead, according to their perceived byte sending rate. We derive condi- tions and a normalisation scheme to ensure that high bandwidth competing flows converge to fair bandwidth allocation regardless of the RTT or segment size used, while maintaining HighSpeed TCP's ability to scale to very high bandwidth environments. We introduce features to preserve TCP friendliness in low bandwidth environments such that, the RTT fairness is no worse than that of standard TCP in scenarios of moderate packet loss. We have conducted simulations to validate the abilities of our proposal to eliminate the RTT bias from HighSpeed TCP. I. INTRODUCTION
Application of adaptive array antennas to radio communications

In the area of mobile communications, there has been increasing demand and development for new technologies and services such as digitization and personalization. With this as background, this paper studies the use of adaptive antenna technology for mobile communication. In the area of mobile communications, the adaptive antenna technology has been studied with a view to reducing the fading for reception by the mobile station. In the case of microcells and indoor communication for which an expanded use is anticipated, arrivals of multiple waves from various directions are expected even for the base station so that the application of the adaptive antennas to the base stations is effective. In the case of high-speed data transmission such as wireless local wireless networks (LAN), further reduction of fading and interference is required. Also, the frequency sharing among different radio services is an area in which the adaptive antenna is useful. Introductions of dynamic control of the systems are expected for mobile communications in time, space, and frequency domains. The adaptive antenna is effective for control in space. The dynamic zone configuration will be a new application area in which, depending on the distributions of the users, the zone shape is varied.
Temporal Factors of EEG and Artificial Neural Network Classifiers of Mental Workload

The use of machine learning algorithms to classify Mental Workload (MW) from various neurophysiological measures is a growing trend in Human Factors research. Several teams have demonstrated that artificial neural networks (ANNs) can be employed to differentiate highly-dimensional neurophysiological data from participants performing tasks at different levels of cognitive demand in many experimental paradigms. Yet, in other cases, classifier performance was found not to exceed chance levels. One inescapable aspect of neurophysiological measures is the time course associated with data collection. This study directly examined the effect of time on classifier performance. Relative classifier performance values were compared for ANNs trained with EEG data from participants performing a verbal/spatial n-back task at varying load levels. For the vast majority of participants, classifiers trained with data from one session were ineffective when tested with data from a subsequent session. Similarly, classification performance suffered when training and testing tasks were incongruent. In contrast to the very high aggregate performance when trained and tested with data from the same session and same task (M = .81), cross-classification performance was consistently much worse (M = .49 – .53). The relative magnitude of the cross-session and cross-task “costs” to classification were compared, revealing a greater effect for session than task. The authors argue that the mere passage of time causes tonic changes in MW-related features of EEG that severely confound ANNs.
Massively parallel processing implementation of the toroidal neural networks

The toroidal neural networks (TNN), recently introduced, are derived from discrete time cellular neural network (DT-CNN) and are characterized by an appealing mathematical description which allows the development of an exact learning algorithm. In this work, after reviewing the underlying theory, we describe the implementation of TNN on the APE100/Quadrics massively parallel system and, through an efficiency figure, we show that such type of synchronous SIMD systems are very well suited to support the TNN (and DT-CNN) computational paradigm.
Eсо-friendly nanotechnologies: synthesis of silver nanoparticles using medicinal plants extracts

Green synthesis of metal nanoparticles (NPs) using plant extracts is a nontoxic and ecofriendly method as compared to chemical and physical methods. The production of nanoparticles with plant extract usage has an important advantages. The aim of our research was to establish the conditions for biogenic synthesis of silver nanoparticles using extracts of the medicinal plants and in vitro cultures of medicinal plants. Plant phenolic compounds with strong oxidation-reduction properties can serve as reducing agents of metal ions to NPs. So for the technology of biogenic synthesis of NPs elaboration the most important stage is to choice the plant which will play a role of «biofactory». The medicinal plants and in vitro cultures of medicinal plants have been screened on the biologically active substances (BAS) content, because BAS are the reducing agents for silver nitrate. The phenolic compounds quantitative content screening have revealed that Silybum marianum, Agastache rugosa, Melittis sarmatica and Digitalis purpurea are the best candidates for NPs synthesis. The various factors affecting on the number of synthesized silver nanoparticles have been determined. These factors are: the concentrations of silver nitrate and reducing agents, the time of synthesis, the temperature and pH of reaction medium. The primary conditions for AgNPs synthesis in Agastache rugosa, Silybum marianum, Melittis sarmatica and Digitalis purpurea extracts have been established. The maximum yield of AgNPs in Agastache rugosa and Digitalis purpurea extracts were observed at 24 C, for Melittis sarmatica — at 35 C and for Silybum marianum extract — at 18 C. The optimal conditions for AgNPs synthesis — pH 9,0 and AgNO3 concentration in solution — 1  10-2 M.
Wyn Johnson and Paula Reimers (2010). Patterns in child phonology . Edinburgh: Edinburgh University Press. Pp. x+270.

Non-disordered acquisition of phonology tends to receive relatively little attention in general texts on language acquisition. The topic is given twelve pages in Guasti’s (2002) book-length language acquisition text, twenty in O’Grady’s (2005) and a single chapter, out of nineteen, in Ritchie & Bhatia’s (1999) child language acquisition handbook (Clark 2009 is an exception, with much more extensive phonological coverage). Johnson & Reimers’ contribution of an entire volume dedicated to the acquisition of phonology (and phonetics) is a welcome and important remedy for this gap. The book begins with a substantial and data-rich chapter on recurring patterns in child phonological production. The patterns surveyed include reduplication, segment and syllable deletion, epenthesis (particularly of onsets and dummy syllables), featural modifications (voicing, stopping/deaffrication, place fronting, gliding) and consonant harmony. For each such pattern, a wide range of cross-linguistic examples is given, along with commentary on the universality (or the lack thereof) of the process among children. In addition, comparisons are made with similar processes in adult grammars, and their degree of attestation. This broad perspective is to be highly commended. Presentation of data first, then explanation and analysis, makes this section a valuable resource for classroom examples and problems. The second chapter, on ‘Strategies’, is in part a continuation of the list of patterns, and in part a demonstration of how some patterns may combine into phonological conspiracies targeting certain outputs (e.g. simplified syllables). The discussion of consonant-cluster simplification is an example of the latter. It is followed by a revisitation of consonant harmony. Additional topics in this chapter are consonant–vowel interactions (discussed very briefly), velar fronting (to coronal) and segmental modification in different positions in the word. The book continues with a chapter on linguistic models of language acquisition, which opens with an attempt to define markedness. The models which are presented are Jakobson’s (1941) framework, Stampe’s Natural Phonology (1972) and then, jumping forward in time, Optimality Theory (Prince & Smolensky 1993). The overarching goal of the chapter is to arbitrate between UG and non-UG approaches to language acquisition. In my view, the authors do little to acknowledge or discuss diversity of opinion and models within each camp. Jakobson’s approach is dismissed as being too strongly predictive of universality, leaving OT as the sole representative of ‘UG’ models. It too is Phonology 29 (2012) 153–156. f Cambridge University Press 2012 doi:10.1017/S0952675712000061
Keystroke Dynamics User Authentication Based on Gaussian Mixture Model and Deep Belief Nets

User authentication using keystroke dynamics offers many advances in the domain of cyber security, including no extra hardware cost, continuous monitoring, and nonintrusiveness. Many algorithms have been proposed in the literature. Here, we introduce two new algorithms to the domain: the Gaussian mixture model with the universal background model (GMM-UBM) and the deep belief nets (DBN). Unlike most existing approaches, which only use genuine users’ data at training time, these two generative model-based approaches leverage data from background users to enhance the model’s discriminative capability without seeing the imposter’s data at training time. These two new algorithms make no assumption about the underlying probability distribution and are fast for training and testing. They can also be extended to free text use cases. Evaluations on the CMU keystroke dynamics benchmark dataset show over 58% reduction in the equal error rate over the best published approaches.
Medical visualization based on VRML technology and its application

Current high-performance computers and advanced image processing capabilities have made the application of three dimensional visualization objects in biomedical images facilitate the researches on biomedical engineering greatly. Trying to cooperate with the update technology using Internet, where 3-D data are typically stored and processed on powerful servers accessible by using TCP/IP, we held the results of the isosurface be applied in medical visualization generally. So in this system we use the 3-D file format VRML2.0, which is used through the Web interface for manipulating 3-D models. In this program we implemented to generate and modify triangular isosurface meshes by marching cubes algorithm, using OpenGL and MFC techniques to render the isosurface and manipulate voxel data. This software is more adequate visualization of volumetric data. The drawbacks are that 3-D image processing on personal computers is rather slow and the set of tools for 3-D visualization is limited. However, these limitations have not affected the applicability of this platform for all the tasks needed in elementary experiments in laboratory or data preprocessed. With the help of OCT and MPE scanning image system, applying these techniques to the visualization of rabbit brain, constructing data sets of hierarchical subdivisions of the cerebral information, we can establish a virtual environment on the World Wide Web for the rabbit brain research from its gross anatomy to its tissue and cellular levels of detail, providng graphical modeling and information management of both the outer and the inner space of the rabbit brain.
Bringing Digital Science Deep Inside the Scientific Article: the Elsevier Article of the Future Project

The ICT revolution of the last decades impacted scientific communication as it has impacted many other forms of communications, changing the way in which articles are delivered and how they can be discovered. However, the impact of ICT on the research itself has been much more profound, introducing digital tools to the way in which researchers gather data, perform analyses, and exchange results. This brought new, digital forms of research output, and disseminating those calls for changes deeply impact the core format of the scientific article. In 2009, Elsevier introduced the “Article of the Future” project to define an optimal way for the dissemination of science in the digital age, and in this paper we discuss three of its key dimensions. First we discuss interlinking scientific articles and research data stored with domain-specific data repositories — such interlinking is essential to interpret both article and data efficiently and correctly. We then present easy-to-use 3D visualization tools embedded in online articles: a key example of how the digital article format adds value to scientific communication and helps readers to better understand research results. The last topic covered in this paper is automatic enrichment of journal articles through text-mining or other methods. Here we share insights from a recent survey on the question: how can we find a balance between creating valuable contextual links, without sacrificing the high-quality, peer-reviewed status of published articles?