Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-native English speaking pre-service teachers in an EFL context: examining experiences through borderland discourse

ABSTRACT This study examined borderland discourse emergent from the practicum experiences of non-native English speaking pre-service teachers (PSTs) in a Thai primary school. Borderland discourse is defined as a space where personal and professional constructs intersect, which is often in a state of dissonance. Over a ten-week practicum period, the PSTs narrated their experiences through a dialogic reflective journal with their teacher-educator. A main issue was the dissonance between PSTs’ expectations with the reality of their teaching context. Some of which were the Thai students’ inability to communicate in English and the use of a syllabus that did not reflect the students’ language abilities. This led to a renegotiation of PSTs’ pedagogical approaches. This study also highlighted potential challenges that non-native English speaking PSTs may face if teaching in a context that is linguistically or culturally different from theirs, as well as a brief account of English language education in Thailand.
A FRAMEWORK FOR PERFORMABILITY MODELLING USING PROXELS

Performability modelling and analysis is used as a measure of both performance and dependability of, mainly, fault-tolerant systems. Proxels are a paradigm that provides deterministic analysis of discrete stochastic models which contain general types of distribution functions, which is not otherwise possible using the standard approaches, such as discrete-event simulation or Markov reward modelling. Because of the flexible definition of the proxels, they can easily be extended to provide a widely-applicable approach to performability modelling. Proxels work in such a way that they track the complete behaviour of the system and correspondingly distribute the probability, depending on the distribution functions and the time spent in each discrete state without anything happening (denoted as age intensity of the state change). Therefore the term state with respect to the proxels has been extended to include the age intensities of the relevant state changes. In this paper we establish the framework for proxel-based performability modelling and analysis, as well as for general reward modelling. Two types of rewards are considered, impulse (associated with transitions) and rate rewards (associated with discrete states). The advantage of the proxel-based simulation is that both types of rewards can be modelled as functions of any other timedependent quantity of the model, and models with general types of distribution functions can be analysed in a deterministic way. For the purpose of demonstrating the method, we will include an example which will show in detail how the method works. Discussion and comparisons with some of the existing approaches will be included too, which will provide more insight into the advantages of the proxel-based method.
Impact of Bias Temperature Instability on Soft Error Susceptibility

In this paper, we address the issue of analyzing the effects of aging mechanisms on ICs' soft error (SE) susceptibility. In particular, we consider bias temperature instability (BTI), namely negative BTI in pMOS transistors and positive BTI in nMOS transistors that are recognized as the most critical aging mechanisms reducing the reliability of ICs. We show that BTI reduces significantly the critical charge of nodes of combinational circuits during their in-field operation, thus increasing the SE susceptibility of the whole IC. We then propose a time dependent model for SE susceptibility evaluation, enabling the use of adaptive SE hardening approaches, based on the ICs lifetime.
Transductive-Inductive Cluster Approximation Via Multivariate Chebyshev Inequality

Approximating adequate number of clusters in multidimensional data is an open area of research, given a level of compromise made on the quality of acceptable results. The manuscript addresses the issue by formulating a transductive inductive learning algorithm which uses multivariate Chebyshev inequality. Considering clustering problem in imaging, theoretical proofs for a particular level of compromise are derived to show the convergence of the reconstruction error to a finite value with increasing (a) number of unseen examples and (b) the number of clusters, respectively. Upper bounds for these error rates are also proved. Non-parametric estimates of these error from a random sample of sequences empirically point to a stable number of clusters. Lastly, the generalization of algorithm can be applied to multidimensional data sets from different fields.
The Development of an Electronic Book on Quantum Phenomena to Enhance Higher-Order Thinking Skills of the Students

This research aims to produce electronic books on quantum phenomena which can be used to enhance the higher-order thinking skills of the students. This research is a development research which used ADDIE method consisting of 5 stages, namely: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. Pre-research data analysis has been collected from 130 students and 4 physics teachers of 3 Senior High Schools in Bandar Lampungby using questionnaire and has been analyzed descriptive-quantitatively. At the design stage, storyboard making was conducted based on the needs of teachers and students in the school as well as the opinion of four experts in physics education. Electronic books on quantum phenomena are deloped with a scientific approach based on indicators of higher-order thinking skills. At the development stage, the realization of electronic book design was carried out and it was then followed by the making of the higher-order thinking skills instrument. The implementation of the electronic was conducted on the students in a class of a Senior High School in Bandar Lampung. The result of the development of the electronic book on quantum phenomena is assessed based on 3 aspects: (1) validity, (2) practicality, and (3) effectiveness. Validity and the practicality of data were obtained by using the validity sheet and questionnaire, effectiveness data were obtained by using higher-order thinking test instrument. Based on the result of data analysis, the product of electronic book on quantum phenomena which is valid, practical, and effective to be used to enhance the higher-order thinking skills of the students.
A generic algorithmic framework for aggregation of spatio-temporal data

Spatio-temporal databases are often associated with analyses that summarize stored data over spatial, temporal or spatio-temporal dimensions. For example, a study of traffic patterns might explore average traffic densities on a road network at different times, over different areas in space, and over different areas in space at different times. The importance of temporal, spatial and spatio-temporal aggregation has been reflected in a significant number of proposals for algorithms for efficient computation of specific kinds of aggregation. However; although such proposals may be effective in particular cases, as yet there is no generic framework that provides efficient support for the wide range of partitioning and aggregation operations that a spatio-temporal database management system might be expected to support over both stored and derived data. This paper proposes an algorithmic framework that can be applied to many different forms of aggregation, and presents the results of performance studies on an implementation of the framework. These show that the framework provides a scalable solution for the many cases in which the aggregations required over stored and derived data may be widely variable and unpredictable.
Topics in Functional and Ecological Vertebrate Morphology : Introduction

Presenting a miscellaneous compilation of papers under the common cover 'Topics in Functional and Ecological Morphology' might be somewhat puzzling at first. On the one hand, such a title suggests a close connection between functional and ecological morphology. On the other hand, it emphasises the distinct nature of both 'disciplines'. In this short introduction we want to argue that this twofold interpretaton of the title is indeed justified. Once denoting separate disciplines, functional and ecological morphology now rather tend to refer to consecutive, practical steps in an integrated evolutionary research program. However, methods still differ considerably.
A Self-Organizing Multi-Channel Medium Access Control (SMMAC) Protocol for Wireless Sensor Networks

This paper proposes a novel multi-channel medium access control (MAC) protocol designed for wireless sensor networks (WSN). Although multiple channel radio communication protocols are well understood in ad hoc wireless and other radio networks, most are not applicable in WSN as sensor nodes which are constrained by low cost and a primitive physical layer. The proposed MAC allows data transmissions take place on multiple channels simultaneously within a single or multiple overlapped radio zones. This MAC applies a light weight, two- tier handshaking algorithm permitting sensor nodes to negotiate a non-occupied channel dynamically. Experimental results show that SMMAC can improve the network performance compared with traditional single channel MAC.
A Novel Linear Recurrent Neural Network for Multivariable System Identification

This paper proposes a novel linear recurrent neural network for multivariable system identification, namely a linerec neural network (LNN). Based on this network, the transfer function matrix model of a multivariable system can be identified directly according to its input and output data. In this way, LNNs differ from existing neural networks. An LNN is constructed based on the identification of prior knowledge in a system, and its weights have definite physical meaning. An LNN is equivalent to a linear equation set, and its training algorithm is based on Widrow-Hoff learning rules. In this paper, the theoretical foundation, structural algorithm and learning rules of LNNs are proposed and studied. To guarantee learning convergence, network training stability is analysed using discrete Lyapunov stability theory. Finally, simulation results show the feasibility of LNNs for multivariable system identification.
The French voter : before and after the 2002 elections

Preface Introduction: French Election Theories and the 2002 Results M.S.Lewis-Beck France's 2002 Presidential Elections: Old and New Territorial Fractures A.Laurent Do Issues Matter? Law and Order in the 2002 French Presidential Election N.Mayer & V.Tiberj Ideology and Party Identification: A Normalization of French Voting Anchors? J.Evans Old Wine in New Bottles? New Wine in Old Bottles? Class, Religion and Vote in the French Electorate B.Cautres Strategic Voting in the 2002 French Presidential Elections A.Blais Institutions and Voters: Structuring Electoral Choice R.Elgie Could There Possibly Have Been Economic Voting? G.Whitten Dual Governance and Economic Voting: France and the United States M.S.Lewis-Beck & R.Nadeau Stuck Between a Rock and a Hard Place: Electoral Dilemmas and Turnout in the 2002 French Legislative Elections T.Gschwend & D.Leuffen Forecasting the 2002 Elections: Lessons From a Political Economy Model B.Jerome & V.Jerome-Speziari Vote Functions in France and the 2002 Election Forecast E.Dubois & C.Fauvelle-Aymar National Economic Voting in France: Objective vs. Subjective Measures E.Belanger & M.S.Lewis-Beck
Building a Cross-lingual Relatedness Thesaurus using a Graph Similarity Measure

The Internet is an ever growing source of information stored in documents of different languages. Hence, cross-lingual resources are needed for more and more NLP applications. This paper presents (i) a graph-based method for creating one such resource and (ii) a resource created using the method, a cross-lingual relatedness thesaurus. Given a word in one language, the thesaurus suggests words in a second language that are semantically related. The method requires two monolingual corpora and a basic dictionary. Our general approach is to build two monolingual word graphs, with nodes representing words and edges representing linguistic relations between words. A bilingual dictionary containing basic vocabulary provides seed translations relating nodes from both graphs. We then use an inter-graph node-similarity algorithm to discover related words. Evaluation with three human judges revealed that 49% of the English and 57% of the German words discovered by our method are semantically related to the target words. We publish two resources in conjunction with this paper. First, noun coordinations extracted from the German and English Wikipedias. Second, the cross-lingual relatedness thesaurus which can be used in experiments involving interactive cross-lingual query expansion.
MR-SPS: Scalable parallel scheduler for YARN/MapReduce platform

In the Big Data era, MapReduce has been the most utilized model in academia and industry. The main objective of MapReduce and its well-known implementation Hadoop is to run distributed applications to analyze huge amount of datasets, on very large clusters of commodity machines. This can be very time consuming. Also, the cluster that runs MapReduce applications has to be very scalable. In order to improve the performance of the MapReduce model, efficient scheduling algorithms have to be developed. Now day, Scalability is a major concern for applications that works on datasets measured by petabytes. Schedulers for such applications must allow a high scalability and an optimal utilization of resources in order to minimize the execution time. For this end we propose MR-SPS, a scalable parallel scheduling algorithm that takes care of scalability of the cluster and its performance by managing workload and data locality. Our scheduler works in a parallel manner, which allows a higher use of the capacities that the Resource-manager can eventually provide, this will increase the number of node that it can manage. For experiments, we have used CloudSim to simulate MR-SPS and other scheduling algorithms designed for MapReduce model. The results show the superiority of our implementation.
Principals changing schools and their career options after principalship: Exploring reasons and options within Malaysian principalship

The issue of principals moving or changing schools has emerged and has been debated within the previous literature that investigates why principals move after a few years of principalship. Based on previous findings, various reasons are listed as motives for principals to move from, or remain at, their current schools. However, within Malaysian principalship, little is known about why principals move to a new school and their options after completing/leaving a principalship position. Thus, this article investigates reasons for moving to second schools and options after the principalship position within the Malaysian context of principalship. For that purpose, nine principals, comprising four middle-phase and five senior principals, were interviewed to solicit their reasons for moving and their options after their principalship phase has been completed. Various factors are mentioned by the principals, such as being posted to schools that are at a distance from their home, providing a platform for a novice principal, and assisting schools that have low achievements. In terms of options after a principalship, senior principals spoke of their intention to remain at the same school until their retirement phase arrives. However, interviewed senior principals revealed their intentions of becoming school leadership consultants as a platform to share their wide experiences with novice principals.
Computationally efficient audio segmentation through a multi-stage BIC approach

In this paper, we propose a computationally efficient approach for unsupervised audio stream segmentation via the Bayesian Information Criterion (BIC). Based on traditional BIC and DISTBIC, a novel multi-stage framework is presented. A statistic mean Euclidean distance based segmentation algorithm is used to pre-select candidate segmentation boundaries, and then delta-BIC integrating energy-based silence detection is employed to perform the segmentation decision to pick the final acoustic changes. Experimental results show that this method can greatly improve the whole detection process speed by a factor of 400 compared to that in Chen's while achieving a 19.2% reduction in the missed detection rate at the expense of a 3.8% increment in the false alarm rate using CCTV news data.
Analysis and optimization of irregular LDPC codes for joint source-channel decoding

In this paper, we present a characterization, through its convergence analysis, and an optimisation of a joint source-channel receiver composed of a LDPC decoder and a Soft Input Soft Output (SISO) source decoder. Under Gaussian approximation, assuming the knowledge of the extrinsic mutual information transfer function (EXIT chart) of the source decoder, we derive the Mutual Information evolution equations, that semianalytically describe the convergence of the iterative system behavior and, to complete the study, the stability condition at the convergence fixed point is derived for the joint receiver. From this analysis, a general optimisation method of the irregularity of the LDPC codes is proposed, which can be reduced to a linear programming optimisation problem. Simulation results show improved performance when compared to an AWGN optimized LDPC code.
Reformulating atmospheric aerosol thermodynamics and hygroscopic growth into fog, haze and clouds

Modeling atmospheric aerosol and cloud microphysics is rather complex, even if chemical and thermodynamical equilibrium is assumed. We show, however, that the thermodynamics can be considerably simplified by reformulating equilibrium to consistently include water, and transform laboratory-based concepts to atmospheric conditions. We generalize the thermodynamic principles that explain hydration and osmosis – merely based on solute solubilities – to explicitly account for the water mass consumed by hydration. As a result, in chemical and thermodynamical equilibrium the relative humidity (RH) suffices to determine the saturation molality, including solute and solvent activities (and activity coefficients), since the water content is fixed by RH for a given aerosol concentration and type. As a consequence, gas/liquid/solid aerosol equilibrium partitioning can be solved analytically and non-iteratively. Our new concept enables an efficient and accurate calculation of the aerosol water mass and directly links the aerosol hygroscopic growth to fog, haze and cloud formation. We apply our new concept in the 3rd Equilibrium Simplified Aerosol Model (EQSAM3) for use in regional and global chemistry-transport and climate models. Its input is limited to the species' solubilities from which a newly introduced stoichiometric coefficient for water is derived. Analogously, we introduce effective stoichiometric coefficients for the solutes to account for complete or incomplete dissociation. We show that these coefficients can be assumed constant over the entire activity range and calculated for various inorganic, organic and non-electrolyte compounds, including alcohols, sugars and dissolved gases. EQSAM3 calculates the aerosol composition and gas/liquid/solid partitioning of mixed inorganic/organic multicomponent solutions and the associated water uptake for almost 100 major compounds. It explicitly accounts for particle hygroscopic growth by computing aerosol properties such as single solute molalities, molal based activities, including activity coefficients for volatile compounds, efflorescence and deliquescence relative humidities of single solute and mixed solutions. Various applications and a model inter-comparison indicate that a) the application is not limited to dilute binary solutions, b) sensitive aerosol properties such as hygroscopic growth and the pH of binary and mixed inorganic/organic salt solutions up to saturation can be computed accurately, and c) aerosol water is central in modeling atmospheric chemistry, visibility, weather and climate.
Competitive PCR for Quantitation of a Cytophaga-Flexibacter-Bacteroides Phylum Bacterium Associated with the Tuber borchii Vittad. Mycelium

ABSTRACT An uncultured bacterium associated with the ectomycorrhizal fungus Tuber borchii Vittad. was identified as a novel member of the Cytophaga-Flexibacter-Bacteroides group. Utilizing a quantitative PCR targeting the 16S rRNA gene, we relatively quantified this bacterium in the host. The estimated number of bacteria was found to be approximately 106 cells per 30-day-old T. borchii mycelium culture. This represents the first molecular attempt to enumerate an uncultured bacterium associated with a mycorrhizal fungus.
Segmentation of heart by using Gabor filter and principal component analysis

Segmentation of the heart across a cardiac cycle is a problem of interest because the left ventricle's proper function, pumping oxygenated blood to the entire body, is vital for normal human activity. Having segmentations of the heart over time allows cardiologists to assess the dynamic behavior of the human heart (using, e.g., the ejection fraction). Segmented heart boundaries can also be useful for further quantitative analysis. Texture features has been widely used in object recognition, image analysis and many others. Gabor filter has emerged as one of the most popular ones. Gabor filter based feature extractor is a Gabor filter defined by its parameters including frequencies, orientations and smooth parameters of Gaussian envelope. Snakes have been used extensively in locating object boundaries. However, in the medical imaging field, many organs in close proximity have similar intensity values, limiting the usefulness of snakes in segmentation of abdominal organs. The gradient vector flow snake is used to test the benefits of running snakes on texture features from orientation based Gabor Filter. A proposed algorithm is GVF (gradient vector Flow) with ASM (Active Shape Model) to overcome several drawbacks in the original framework. The algorithm is completely automatic and computationally efficient.
IDENTIFYING A THRESHOLD CHOICE FOR THE SEARCH ENGINE USERS TO REDUCE THE INFORMATION OVERLOAD USING LINK BASED REPLICA REMOVAL IN PERSONALIZED SEARCH ENGINE USER PROFILE

The search engine information over load reduction has been focused and presented in the paper. The replica of cluster content, hyperlinks and sub-hyperlinks in the personalized user profile have been removed to reduce the information overload. This has been carried out through a personalized search results against existing query cluster's method. It has been found that the user profile with replication has more information overload than non-replicated profile. The experimental result performed by Lingo algorithm with few threshold values after finding the word weight of all content and pre-processing. The result findings confirm that the negative impact on cluster content and positive impact over sub-hyperlinks at the same time and no impact on hyperlinks. In order to measure the performance , few choices of the threshold result findings have been confirmed for the better results. The student t-test is used for analysis, and it confirms that the variations before and after removal of cluster and link based replica content in all the threshold levels.