Miracle-dz/UniFAR-FTUs huggingface dataset:
LOCALIZED OSCILLATIONS IN NONLINEAR LATTICES : EXISTENCE AND STABILITY

Numerical methods using homoclinic orbits are applied to study the existence and stability of spatially localized and time-periodic oscillations of 1-dimensional (1D) nonlinear lattices, with linear interaction between nearest neighbors and a quartic on – site potential 4 2 4 1 2 1 ) ( u Ku u V ± = where the ( + ) sign corresponds to “hard spring” and ( ) to “soft spring” models. These localized oscillations when they are stable under small perturbations are very important for physical systems, since they seriously affect the energy transport properties of the lattice. We use Floquet theory to analyze their linear (local) stability, along certain curves in parameter space (α, ω), where α is the coupling constant and ω the frequency of the breather. We then apply the Smaller Alignment Index method (SALI) to investigate more globally their stability properties in phase space. Comparing our results for the ± cases of V(u), we find that the regions of existence and stability for simple breathers of the “hard spring” lattice are considerably larger than those of the “soft spring” system. The variation of the size of the regular region around a stable breather is investigated as the number of particles is increased.
Challenges in Delivering Software in the Cloud as Microservices

Microservices can be broadly defined as the design of service-oriented software using a set of small services. In a microservice architecture, application complexity is distributed among narrowly focused and independently deployable units of computation. Such complexity can result in security vulnerabilities. Trustworthiness is also an issue when dealing with microservices. Moreover, there may be gaps in existing legal frameworks with regard to this technology. Solutions to these issues must seek balance between security and performance.
A novel global self-timing methodology for BSFQ circuits

Recently we have proposed Boolean single-flux-quantum (BSFQ) circuits, which like CMOS circuits directly support Boolean primitives, and do not require local synchronization for their elementary cells as well as for their combinational cells. However, only the cell-level timing description of the BSFQ circuits was considered, which did not specify their global timing strategy in a system-level design. In this paper, we present a novel global self-timing methodology, dual encoding hierarchical pipelining (DEHP), for the locally asynchronous BSFQ circuits. In circuit implementation, a nonvolatile memory cell named ND-DFF and a volatile memory cell named D-DFF have been designed.
Teaching programming paradigms and languages for qualitative learning

Effective quality management in teaching and learning can be implemented by careful planning of the subject delivery system, active student involvement and continuous evaluation system in the classroom. In this papel; we discuss the issues involved with the quality improvement of teaching and learning various programming paradigms and languages. Our main aim is to prepare students with analytical abilities in choosing the most appropriate programming language to implement a given software-based system in their future professions. We believe that the qualitative learning of programming language plays an important role in improving the quality of the sofrware products and in furthering the development of the profession. The paper first presents some arguments in light of the current literature on computer science education and quality in higher education, and then, discusses a simple model of teaching and learning that we have adopted in this subject.
The Portuguese Escudo in the ERM

The European Union (EU) will be enlarged to 10 new Member-States in May 2004. Upon accession to the EU, these countries are required to treat their exchange rate policies as a matter of common interest and to pursue price stability as the primary objective of monetary policy. In addition, the new Member States have committed to adopt the euro upon the fulfilment of the required convergence criteria. Against this background, many acceding countries have signalled their intention to join the Exchange Rate Mechanism II (ERM II)(1). The mechanism can provide a useful framework for the conduct of monetary and exchange rate policies in the new Member States and is also a precondition for joining the euro. This article reviews the experience of the Portuguese escudo in the exchange rate mechanism (ERM) of the European Monetary System (EMS), the precursor of ERM II. The Portuguese experience will hopefully provide a useful point of reference for the acceding countries as they consider applying for ERM II membership. Section 2 discusses the background to the decision to apply for ERM membership. Section 3 describes the management of the escudo in the ERM, highlighting three distinct periods. The first period corresponds to the early months of participation in the system, from April to the summer 1992, i.e. the last phase of the “hard EMS”. The second period coincided with the ERM crisis, which started in the summer of 1992 and ultimately led to a widening of the fluctuation bands to +15 per cent in August 1993. Finally, the third period, from the enlargement of the ERM bands to the end of 1998, was one of increasing stability in the run-up to Economic and Monetary Union (EMU). Section 4 concludes.
Smad regulation in TGF-β signal transduction

Members of the transforming growth factor-β (TGF-β) family control growth, differentiation and apoptosis of cells, and have important functions during embryonic development (Derynck et al., 2001; Massagué et al., 2000; Whitman, 1998). The human genome encodes 28 genes that encode members of this family (Venter et al., 2001), including TGF-β isoforms, activins and bone morphogenetic proteins (BMPs). These proteins signal by stimulating formation of specific heteromeric complexes of type I and type II serine/threonine kinase receptors. The type II receptors are encoded by five known mammalian genes, bind to ligands, and phosphorylate and activate the type I receptors, of which there are seven mammalian members (Fig. 1). The available data support the notion that the type I receptors are responsible for the specificity of downstream signalling. The ligands, receptors and their intracellular effectors, the Smads, are conserved in eukaryotes from Caenorhabditis elegans and Drosophila to Here, we review the mechanisms by which Smad signalling is regulated, that is, how Smad molecules are activated, translocated to the nucleus, interact with other nuclear partners and how they are degraded.
Context-Aware Service Overlay Network: Concept and Case Study

There have been several efforts to provide service-aware technologies in the networks, such as Service-Oriented Architecture (SOA) and Service Delivery Platform (SDP). These technologies were integrated with Service Overlay Network (SON) infrastructure to support control and delivery of services over multiple network domains. However, SON has the limitations of handling the increasing need of ubiquitous and dynamic environment of users and services. To provide better Quality of Experience (QoE) to users in the ubiquitous and dynamic environment, we advocate the notion of Context-aware SON (CSON) to support context-aware and dynamically adaptive service delivery and control. In this paper, we introduce the concept of CSON, and provide a comprehensive review of the basic ideas by visiting our experiences on designing and developing a prototype for CSON.
Going Beyond the Millennium Ecosystem Assessment: An Index System of Human Dependence on Ecosystem Services

The Millennium Ecosystem Assessment (MA) estimated that two thirds of ecosystem services on the earth have degraded or are in decline due to the unprecedented scale of human activities during recent decades. These changes will have tremendous consequences for human well-being, and offer both risks and opportunities for a wide range of stakeholders. Yet these risks and opportunities have not been well managed due in part to the lack of quantitative understanding of human dependence on ecosystem services. Here, we propose an index of dependence on ecosystem services (IDES) system to quantify human dependence on ecosystem services. We demonstrate the construction of the IDES system using household survey data. We show that the overall index and sub-indices can reflect the general pattern of households' dependences on ecosystem services, and their variations across time, space, and different forms of capital (i.e., natural, human, financial, manufactured, and social capitals). We support the proposition that the poor are more dependent on ecosystem services and further generalize this proposition by arguing that those disadvantaged groups who possess low levels of any form of capital except for natural capital are more dependent on ecosystem services than those with greater control of capital. The higher value of the overall IDES or sub-index represents the higher dependence on the corresponding ecosystem services, and thus the higher vulnerability to the degradation or decline of corresponding ecosystem services. The IDES system improves our understanding of human dependence on ecosystem services. It also provides insights into strategies for alleviating poverty, for targeting priority groups of conservation programs, and for managing risks and opportunities due to changes of ecosystem services at multiple scales.
Learning Out-of-Vocabulary Words in Automatic Speech Recognition

Out-of-vocabulary (OOV) words are unknown words that appear in the testing speech but not in the recognition vocabulary. They are usually important content words such as names and locations which contain information crucial to the success of many speech recognition tasks. However, most speech recognition systems are closed-vocabulary recognizers that only recognize words in a fixed finite vocabulary. When there are OOV words in the testing speech, such systems cannot identify OOV words, but misrecognize them as in-vocabulary (IV) words. Furthermore, the errors made on OOV words also affect the recognition accuracy of their surrounding IV words. Therefore, speech recognition systems in which OOV words can be detected and recovered are of great interest. As simply applying a large vocabulary in a recognizer cannot solve the OOV word problem, several alternative approaches had been proposed. One is to use a hybrid lexicon and hybrid language model which incorporate both word and sublexical units during decoding. Another popular OOV word detection method is to locate where the word decoding and the phone decoding results are in disagreement. Some other methods involve with a classification process to find possible OOV words using confidence scores and other evidence. For OOV word recovery, the phoneme-to-grapheme (P2G) conversion is usually applied to predict the written form of an OOV word. Current OOV research focuses on detecting the presence of OOV words in the testing speech. There is only limited work about how to convert OOV words into IV words of a recognizer. In this thesis, we therefore investigated learning OOV words in speech recognition. We showed that it is feasible for a recognizer to automatically learn new words and operate on an open vocabulary. Specifically, we built an OOV word learning framework which consists of three major components. The first component is OOV word detection, where we built hybrid systems using different sub-lexical units to detect OOV words during decoding. We also studied to improve the hybrid system performance using system combination and OOV word classification techniques. Since OOV words can appear more than once in a conversation or over a period of time, in the OOV word clustering component, we worked on finding multiple instances of the same OOV word. At last, in OOV word recovery, we explored how to integrate identified OOV words into the recognizer’s lexicon and language model. The proposed work was tested on tasks with different speaking styles and recording conditions including the Wall Street Journal (WSJ), Broadcast News (BN), and Switchboard (SWB) datasets. Our experimental results show that we are able to detect and recover up to 40% OOV words using the proposed OOV word learning framework. Finally, a self-learning speech recognition system will be more robust and has broader applications in real life.
Feature Extraction of Currency Notes: An Approach Based on Wavelet Transform

In this paper, we propose to extract the texture features of currency note images. To extract the features, first the Discrete Wavelet Transform (DWT) in particular Daubechies 1 (DB1) is utilized on a currency note and the approximate coefficient matrix of the transformed image is obtained. A set of coefficient statistical moments are then extracted from the approximate efficient matrix. The extracted features are stored in a feature vector. The extracted features can be used for recognition, classification and retrieval of currency notes.
The black hole mass, Eddington ratio and MBH–σ[O iii] relation in young radio galaxies

The masses of the central supermassive black holes (BHs) and the Eddington ratios for a sample of 65 young radio galaxies [27 gigahertz-peaked spectrum (GPS) and 38 compact steep-spectrum (CSS) sources] are estimated by various methods. We find that the average BH mass of these young radio galaxies is (log M BH ) ≃ 8.3, which is less than that of radio loud quasi-stellar objects (QSOs) and low-redshift radio galaxies ((log M BH > ≃ 9.0). The CSS/GPS sources have relatively high Eddington ratios with average ratio (log L bol /L Edd > = ―0.56, which are similar to those of narrow-line Seyfert 1 galaxies (NLSls). It suggests that the CSS/GPS sources may not only be in the early stage of radio activities, but also in the early stage of their accretion activities. We find that the young radio galaxies as a class deviate systematically from the M BH ―σ * relation defined by nearby inactive galaxies, when using σ [O III as a surrogate for the stellar velocity dispersion σ * . There is no significant correlation between the deviation of the [O m] emission line width, Δσ ≡ σ [OIII] ― σ [pred] and the jet/accretion power, where σ [pred] are calculated from the Tremaine et al. relation using the estimated BH masses. However, we find that the deviation Δσ in young radio galaxies is well correlated with the Eddington ratio, and this correlation is found to be similar to that of radio quiet active galactic nuclei (AGN) (QSOs/NLSls) where the radio jet is absent or weak. We suggest that the accretion activities may still play an important role in shaping the kinematics of [O III] narrow line in these young radio galaxies.
Flash SSD vs HDD: High performance oriented modern embedded and multimedia storage systems

Flash memory is continuously been dominating on HDD for performance oriented modern applications by last more than two decades. Currently the high capacity MLC flash SSDs are becoming center of attraction for large size multimedia systems to support their increasing storage and throughput demands. The advantage of MLC flash over SLC flash is lower cost, higher capacity and increased throughput. However, MLC flash SSDs suffer for lesser data reliability, higher bit error ratio and reduced erasure cycles compare to SLC flash SSDs. In this paper, the performance is evaluated and compared of both types of NAND flash memories with HDD. Experimental results based on two modern real-time benchmarks are provided and discussed to give the better idea to users for suitable storage devices for their embedded and multimedia applications.
Cortical Neural Prosthetics

Prosthetic arms are man-made appendages used to replace missing or defective limbs. Traditional, non-robotic prosthetic arms can be cheap and effective replacements; however, Cortical Neural Prosthetics (CNPs) are a form of robotic prosthesis which allow for more biocompatibility with other body parts and the environment, and are more easily controlled [11]. Though these qualities are not necessary for basic prosthetic functionality, prosthetic users typically desire the more dynamic and realistic nature of CNPs. With refinement, CNP arms can provide dynamic and realistic arm motion to people without arms, allowing them to interact with other people and their environment in a natural and easily controlled manner. CNPs record neural activity in the brain, transform that activity into arm movement signals, and then signal a mechanical actuator to make those movements. Recording electrodes discriminate electric neural signals in the motor cortex of the brain, where arm motion is controlled. Extraction algorithms take these signals from an array of sites in the motor cortex and convert them to end point (hand) positions of a prosthetic arm. With this algorithmic transformation, an actuator causes the desired mechanical change in position of the prosthetic limb. CNP control is optimal when this cycle occurs continuously in real time [11]. Successful CNP use has been demonstrated with self-feeding monkeys, but further refinement is needed before CNPs can become clinically available [14]. Complications with CNPs arise primarily through tissue rejection of microprobes, causing poor signal quality over time. Also, the algorithmic transformation from brain signals to an end point position is highly complex due to continuous and unclear signaling in the brain. Finally, the output of an extraction algorithm must be understood by the subject in such a way that they can alter their neural activity to generate more fluid and precise movement with practice over time [11]. Work is currently being done to improve the microelectrode-tissue interface, and algorithms are being refined. Closed-loop cognitive feedback systems, where subjects adapt their neural networks to refine their movements, are also being investigated [10]. An overview of CNP signal recording and extraction algorithm systems, the user requirements for these systems, and an overview of past experimentation and future directions for CNP refinement are provided in this paper. The main challenge for CNP development is making technologically advanced components that fulfill user needs in a safe and effective manner.
A XML-based composite event approach

Content-based Pub/sub system offers a convenient abstraction for information producers and consumers, supporting a large-scale system design and evolution by integrating several distributed independent application systems. However, existing content-based Pub/Sub systems mainly focus on the "one-to-one" event matching, not on the composite event matching. The composite event matching enables application components to express more interest in the occurrence of event composite patterns. In this paper, we present a XML-based composite event model that consists of the temporal logical model and the event composite pattern. Based on the composite event model, a subscription language (EXML-QL) is introduced by extending XML-QL language to support the XML-based composite event computing. Finally, according to the peculiarities of the subscription language, a composite event matching algorithm is presented and analyzed.
Rotation Invariant Common Sketch Extraction

In this paper, we present a new method to sketch the common among several images. Our method captures rotation invariance by extending the local self descriptor to rotation invariance and proposes a easy method to detect a roughly similar region across the images. Our method is composed of three stages: (i) Detecting a similar region which the proportion of the common is as large as possible across the images. (ii) Estimating the rotation angle by matching the descriptors across the similar region, then aligning the images. (iii) Generating a clean and compact binary sketch. The experiments demonstrate that our method can handle the rotation between common and obtain a clear common sketch.
Robust phone set mapping using decision tree clustering for cross-lingual phone recognition

Recently, research related to multi-lingual and cross-lingual speech has gained increasing popularity. One of the major problems when dealing with multi-lingual speech data is the mapping of the phone sets between different languages. Phone mapping is useful for cross-lingual speech recognition, cross-lingual pronunciation modelling and mixed language speech synthesis, to name a few. In this paper, an automatic context sensitive phone set mapping method is presented to improve the mapping accuracy. A training methodology that allows the mapping to be learned automatically from parallel time-aligned phone transcriptions is also described. In particular, a decision tree clustering technique is used to tie unseen contexts for robustness. The quality of the proposed mapping method is evaluated on a cross-lingual phone recognition task where the Hungarian and Russian phone recognisers are used to recognise Czech speech and produce Czech phone sequences through phone set mapping. The mapping was trained on only a small amount of data. A consistent relative improvement of 5 - 7% is reported when contextual information is added to phone set mapping.
The Accuracy of Non‐traditional versus Traditional Methods of Forecasting Lumpy Demand

Forecasting for inventory items with lumpy demand is difficult because of infrequent nonzero demands with high variability. This article developed two methods to forecast lumpy demand: an optimally weighted moving average method and an intelligent pattern-seeking method. We compare them with a number of well-referenced methods typically applied over the last 30 years in forecasting intermittent or lumpy demand. The comparison is conducted over about 200,000 forecasts (using 1-day-ahead and 5-day-ahead review periods) for 24 series of actual product demands across four different error measures. One of the most important findings of our study is that the two non-traditional methods perform better overall than the traditional methods. We summarize results and discuss managerial implications. Copyright © 2011 John Wiley & Sons, Ltd.
Finding minimum locating arrays using a CSP solver

Combinatorial interaction testing is an efficient software testing strategy. If all interactions among test parameters or factors needed to be covered, the size of a required test suite would be prohibitively large. In contrast, this strategy only requires covering $t$-wise interactions where $t$ is typically very small. As a result, it becomes possible to significantly reduce test suite size. Locating arrays aim to enhance the ability of combinatorial interaction testing. In particular, $(\overline{1}, t)$-locating arrays can not only execute all $t$-way interactions but also identify, if any, which of the interactions causes a failure. In spite of this useful property, there is only limited research either on how to generate locating arrays or on their minimum sizes. In this paper, we propose an approach to generating minimum locating arrays. In the approach, the problem of finding a locating array consisting of $N$ tests is represented as a Constraint Satisfaction Problem (CSP) instance, which is in turn solved by a modern CSP solver. The results of using the proposed approach reveal many $(\overline{1}, t)$-locating arrays that are smallest known so far. In addition, some of these arrays are proved to be minimum.
How Chinese firms employ open innovation to strengthen their innovative performance

China became the second-largest economy behind the USA in 2010. While there is quite some macroeconomic research documenting the technological catching-up of China as a nation, there is only little research studying how individual Chinese firms are catching up. This paper draws on the open innovation perspective to explore how Chinese firms improve their innovative performance. Our empirical analysis is based on a sample of 91 native Chinese firms in high-tech industries. The results indicate that Chinese