Miracle-dz/UniFAR-FTUs huggingface dataset:
Matching for Robust Speech Rec

Abstruct- We present a maximum-likelihood (ML) stochastic matching approach to decrease the acoustic mismatch between a test utterance and a given set of speech models so as to reduce the recognition performance degradation caused by distortions in the test utterance and/or the model set. We assume that the speech signal is modeled by a set of subword hidden Markov models (HMM) Ax. The mismatch between the observed test utterance Y and the models Ax can be reduced in two ways: 1) by an inverse distortion function Fv(.) that maps Y into an utterance X that matches better with the models Axand 2) by a model transformation function Gv(.) that maps Ax to the transformed model Ay that matches better with the utterance Y. We assume the functional form of the transformations F, (.) or GT(.) and estimate the parameters v or 7 in a MI, manner using the expectation-maximization (EM) algorithm. The choice of the form of F, (.) or G, (.) is based on our prior knowledge of the nature of the acoustic mismatch. The stochastic matching algorithm operates only on the given test utterance and the given set of speech models, and no additional training data is required for the estimation of the mismatch prior to actual testing. Experimental results are presented to stndy the properties of the proposed algorithm and to verify the efficacy of the approach in improving the performance of a HMM-based continuous speech recognition system in the presence of mismatch due to different transducers and transmission channels. The proposed stochastic matching algorithm is found to converge fast. Further, the recognition performance in mismatched conditions is greatly improved, while the performance in matched conditions is well maintained. The stochastic matching algorithm was able to ,reduce the word error rate by about 70% in mismatched conditions.
Extracting fault subspaces for fault identification of a polyester film process

Although fault detection has been well studied in process monitoring under stationary conditions, the identification of faults in chemical processes is a difficult task. We present a new approach in the use of a fault identification index to identify faults based on fault directions extracted from abnormal data using singular value decomposition. The proposed method is demonstrated on an industrial polyester film process which is characterized by frequent set-point changes and multiple grade changes. Further, a comparison between the fault identification index and the contribution plot method is given.
On different types of clitic clusters

In this paper, Italian and Bantu clitic clusters are analyzed and compared. I claim that in both language families, pronouns check case in a low clitic position, and in so doing they reverse the order of arguments. In Italian, clitics move to a high clitic position where they check person and number features. Different types of Italian clusters are individuated: they differ syntactically, phonologically, and morphologically. As in Kayne’s (1994) proposal, clusters can be formed either on one single functional head or on adjacent heads; the former type can appear both in enclisis and proclisis, the latter only in proclisis. Clitic pronouns can end with an epenthetic vowel or a class marker/ inflectional morpheme; the former (consonantal clitics) can appear in clitic clusters in any position, the latter (morphologically complex clitics) cannot be the first element in clitic clusters dominated by one single head. Finally, some clusters are inserted as lexical units, others are two independent words: only the former display the linking vowel [e]. The intricate interplay of these (partially) independent properties explains a number of restrictions on clusters found in Italian (and other Romance languages). The hierarchy of person and number features in the high clitic position is also discussed, which explains other restrictions on clusters.
Exploiting user-generated data for knowledge discovery and recommendation

The Internet and Web 2.0 have achieved a rapid growth and became ubiquitous in recent years. The advance in information technologies has also enabled users to generate data, implicitly or explicitly, on an unprecedented scale. Consequently, the need to discover and exploit new and useful knowledge from such data has also increased considerably. In this thesis, in this regard, we investigate user-generated data to discover interesting knowledge and enable better recommendation services. First, we tackle the problem of the location type classification using individual Twitter messages. We extend probabilistic text classification models to incorporate temporal features and user history information as probabilistic priors, and show that the proposed models can boost the classification accuracy effectively. Second, we study the problem of quantifying the notion of political legitimacy using collective Twitter messages for specific populaces. We design a framework that aggregates a large number of tweets into the final legitimacy score of a populace by leveraging probabilistic topic modeling and sentiment analysis technique. Our empirical evaluation on eight sample countries using related public tweets demonstrates that our proposed framework shows a strong correlation to results reported in political science literature. We also apply this framework to a traditional news media data set, and compare the results with Twitter data. Several interesting differences are discovered between these two medias for this quantification task of political legitimacy. Third, we study the problem of mining implicit user feedback in recommendation systems. In particular, we tackle the cold-start problem of video recommendation using users’ co-view information. We propose a classification framework to incorporate co-view information based on previously seen video pairs, and learn the weights of video attributes for ranking candidate videos to recommend, yielding encouraging recommendation results.
A transparent collaborative framework for efficient data analysis and knowledge annotation on the web

High-throughput experiments and ultrascale computing generate scientific data of growing size and complexity. These trends challenge traditional data analysis environments, most of which are based on scripting languages such as R, MATLAB or IDL, in a number of ways. To address some of these challenges, this research proposes a framework with the overarching goal to enable large-scale high-performance data analytics and collaborative knowledge annotation over the Web. The proposed framework has three major components, which parallel the three core steps of the knowledge discovery cycle. (1) For the first step, defining the data analysis pipeline, the research designs and implements a Web-enabled interactive and collaborative statistical R-based environment. The component implements a memory management system that minimizes memory requirements thereby enabling multi-user scalability. To the best of our knowledge, this is the first Web-enabled R system that supports interactive remote access to R servers and enables users to share data, results and analysis sessions. (2) For the second step, executing the data analysis pipeline, the research investigates and proposes a transparent and low-overhead means for executing external compiled language parallel codes from within R, thus seamlessly bridging two code development paradigms: efficient, compiled parallel codes and high abstraction and easy-to-use scripting codes. This component contains three elements: a transparent bidirectional translation of data objects between R and compiled languages, such as C/C++/Fortran; seamless integration of external parallel codes; and automatic parallelization of data-parallel computations in hybrid multi-core and multi-node execution environments. (3) For the third step, annotating the predictive knowledge derived from community analysis pipelines, the research explores an environment for semantically rich, structured and queriable annotation of facts, relationships between those facts, and complex events reported in scientific literature. The social networking nature of this component allows the community to improve the predictions as well as generate new, higher-level inferences, thus rolling in the gaps in the communities' understanding of physical phenomena. The environment offers mechanisms for streamlining the annotated and curated knowledge into distributed public databases, thus enabling a feedback loop into the database-publication cycle to allow scientists to make connections between data-driven predictions and published evidence.
Optimal training signals for MIMO OFDM channel estimation in the presence of frequency offset and phase noise

We develop robust mean-square error (MSE)-optimal training signal designs for multiple-input multiple-output orthogonal frequency-division multiplexing channel estimation with frequency offset and phase noise (PN), and present analytical and simulation results for the frequency-offset and PN effects on channel estimation. The proposed designs are more advantageous for moderate-to-high values of signal-to-noise ratio (SNR), residual frequency offset, and PN level. At SNR = 10 dB, the normalized MSE reductions of our proposed training signals at normalized frequency offset |v|=0.1,0.5 are about 9 and 19 dB, respectively, for one transmit antenna, and 6 and 11 dB for two transmit antennas
Exploring the Material Conditions of Learning: Opportunities and Challenges for CSCL

In CSCL studies, language is often foregrounded as the primary resource for engaging in collaborative learning, while the body is more often positioned as a secondary resource. In this paper, we present, analyse and discuss how two nine-year-old children collaborate through gesturing and moving their bodies around a touchscreen. The pair is working with the concept of scale and are in midst of copying their rooms from paper to touchscreen. During this process, the pair engages in a discussion regarding the size of one meter through language, gestures and manipulation of the material resource. The analysis shows two distinct ways of understanding the length of one meter, which primarily is visible through the children‟s gesturing and bodily movement. In conclusion, the analysis shows that children dynamically produce body-material resources for communicative and illustrative purposes; moreover, they use body-material as a cognitive tool and as a way of shepherding the other.
Comparative performance analysis of AODV and DSR routing protocols in MANET

This Mobile Ad-hoc Network (MANET) is a wireless network without infrastructure and centralized administration. Since there is a random and dynamic change in network topology due to the mobility of host, therefore the need for a robust dynamic routing protocol is required. Consequently this paper presents a comparative study between two routing protocols DSR and AODV. Both protocols were compared in terms of packet delivery ratio, average end-to-end delay, Throughput and Normalized routing load.
Towards a more efficient EFL reading comprehension classroom environment: The role of content and critical reading

Traditional reading comprehension methods background the sometimes controversial content of texts in the interest of ‘ensuring comprehension’ via dealing with language points. According to Wallace (1992), EFL learners are often marginalized as readers; their goals in interacting with written texts are perceived to be primarily those of language learners. This study explores how a change in teaching approach via a CDA framework along with a change in reading content affects the EFL students’ perceptions of their reading comprehension classroom environment. Through a one-group pretest posttest design, the What Is Happening In This Class? (WIHIC) questionnaire was distributed twice among 41 (F=23 and M=18) Iranian EFL students, the first time after a five-sessionlong regular non-critical reading comprehension class and the other time after a fivesession-long reading comprehension class featured by more involving passages and informed by a CDA framework proposed by Cots (2006). The data were analyzed using SPSS and the results showed that there was a significant difference (p<0.05) between the participants’ perceptions of each dimension (i.e, Student cohesiveness, Teacher support, Involvement, Task orientation, Cooperation, and Equity) of their reading comprehension classroom before and after introducing the CDA techniques and changing the content of the reading materials. The change in teaching approach via the CDA framework and the change into more involving content led to a reading comprehension classroom environment that was perceived by students as more efficient and facilitative of learning.
Impacts of Trapezoidal Fin of 20-nm Double-Gate FinFET on the Electrical Characteristics of Circuits

In this study, we analyze the impacts of the trapezoidal fin shape of a double-gate FinFET on the electrical characteristics of circuits. The trapezoidal nature of a fin body is generated by varying the angle of the sidewall of the FinFET. A technology computeraided-design (TCAD) simulation shows that the onstate current increases, and the capacitance becomes larger, as the bottom fin width increases. Several circuit performance metrics for both digital and analog circuits, such as the fan-out 4 (FO4) delay, ring oscillator (RO) frequency, and cut-off frequency, are evaluated with mixed-mode simulations using the 3D TCAD tool. The trapezoidal nature of the FinFET results in different effects on the driving current and gate capacitance. As a result, the propagation delay of an inverter decreases as the angle increases because of the higher on-current, and the FO4 speed and RO frequency increase as the angle increases but decrease for wider angles because of the higher impact on the capacitance rather than the driving strength. Finally, the simulation reveals that the trapezoidal angle range from 10° to 20° is a good tradeoff between larger on-current and higher capacitance for an optimum trapezoidal FinFET shape.
Instructional Strategies: What Do Online Students Prefer?

This study examined student opinions and preferences regarding the impact of six varied instructional strategies in an online graduate curriculum course. The primary research questions were 1) Which online instructional module did students most prefer? 2) Which online instructional module did students least prefer? Students enrolled in two curriculum courses in a Master’s of Art in Education program rated the instructional strategies in the online courses and described their most and least preferred technique. All participants were female and included both pre­service and in­service teachers. Data were gathered through student reflections and a survey administered at the conclusion of the class. Student reflections were coded for themes while survey data was analyzed for frequency counts. Results indicated that students preferred independent, passive modes of instruction in online courses because of ease, convenience, and comfort level. Overall reflections indicated student appreciation of a mix of instructional strategies that incorporated more interactive technological modes of instruction with independent, passive modes of instruction. These findings suggest when developing online courses, university professors not assume one instructional strategy fits all. As a result, online courses should provide a balance of instructional approaches.
Performance Evaluation of OFDM System for Different Modulation Techniques on the basis of Bit Error Rate and Peak to Average Power Ratio

Orthogonal frequency division multiplexing (OFDM) is a form of digital modulation used in a wide array of communication systems. This paper presents a comprehensive performance analysis of orthogonal frequency division multiplexing system. We investigate the basic principle of OFDM system and through computer simulation we present the Bit error rate(BER) and peak-to-average power ratio(PAPR) of OFDM system for different modulation techniques.
VLSI placement with pre-placed modules based on less flexibility first principles

The locations of ROM, RAM, and CPU often were required to fix a priori while other modules are subject to be placed in the rest of the chip area. These situations were formulated as placement with pre-placed modules. Rectilinear substrate and holes of the substrate can be also modeled with the use of pre-placed modules. Unlike the coding scheme based stochastic optimization placement algorithms, which need special feasible checking of the representation for placement with pre-placed modules, we develop a new deterministic algorithm to cope with the same problem. The placement area is evaluated first. Then the flexibility of each placement module is calculated according to its packing location, size and connectivity among other neighbor modules. According to the less flexibility first principle, the placement is completed through a recursive packing process. Pre-placed modules just form the placement area, no extra calculation is needed. Experiment results show our algorithm is better than stochastic algorithm.
Error Analysis of English Translation of Islamic Texts by Iranian Translators

With the rise of Translation Studies as a new science, translation error assessment has moved toward more scientific approaches, and the related frameworks proposed for error identification and assessment are integrated more and more.Errors emerge as the result of some factors. Three main perspectives are involved in each translation which includes: culture, syntax and semantics. Therefore, translation errors occur as the result of incompetence in one or more than one of these categories. Given the importance and the precision required in the translation of religious texts, this research, aimed at the analysis of the type and frequency of the errors occurring in the English translation of Islamic texts by Iranian translators and analyze the possible cause of the errors. To this end, 9 Islamic texts and their English translations were selected. Then, using Morgan’s sample selection table, The errors were categorized based on the classification of error types developed by Liao (2010). The results of the study revealed that the register category was the most frequent error area.
Precoder for DMT with insufficient cyclic prefix

Multi-carrier modulation is a modulation technique that enables higher transmission rate than traditional techniques, such as single-carrier quadrature amplitude modulation (QAM) systems. One implementation of multi-carrier modulation technique is discrete multi-tone (DMT). DMT used in asymmetric digital subscriber lines (ADSL) and very high speed DSL (VDSL) systems has a fixed cyclic prefix length. When the impulse response of the channel is longer than the designed prefix length, for instance when the length of the line impulse response is very long, distortion will appear at the channel output in the form of interference between the carriers. This paper describes a method to remove this distortion by introducing a precoder at the transmitter. Although there will be a power increase when the precoder is used, the distortion is significantly reduced, yielding a performance improvement.
The Relationship between Computer-Based Concept Mapping and Creative Performance

The intent of this study is to explore the relationship between computer-based concept mapping and creative performance. Concept mapping is a method of graphical learning that can be beneficial as a study method for concept linking and organization. Technological progress has advanced concept mapping to computerized forms. This research explores computer-based concept mapping as a creative tool to improve students' creative performance. This study examined forty students in the design department at technical universities to analyze whether computer-based concept mapping and applications improved students' video production and creative performance. The results show that (1) the application of computer-based concept mapping received approval from students; (2) students' computer-based concept mapping performance is directly related to their video production performance; and (3) students' computer-based concept mapping performance can effectively predict their creative performance.
10. RESEARCH PERSPECTIVES ON TEACHING ENGLISH AS A LINGUA FRANCA

This chapter shows just how deeply affected English has already been through its unprecedented spread, and the unique function it has as the world language. It argues, however, that it would be premature to launch into a discussion of the teaching of this lingua franca before certain prerequisites have been met. The most important of these are a conceptualization of speakers of lingua franca English as language users in their own right, and the acknowledgment of the legitimacy of, and indeed the need for, a description of salient features of English as a lingua franca (ELF), alongside English as a native language (ENL). The presentation summarizes the empirical research into the lingua franca use of English, which has recently gathered considerable momentum. It sets this research in relation to other relevant work in descriptive linguistics, sociolinguistics, and applied linguistics for language pedagogy. Finally, it discusses the implications of this historically unique situation for potential developments in the pedagogy of English teaching and outlines some research questions that must be addressed if advances in the teaching of English as a lingua franca are to have a secure theoretical and descriptive base.
Examination of Elementary Teachers' Views about Concept Maps

One of the teaching methods that are carried out to make teaching-learning process more effective is concept mapping. Learners can incorporate new knowledge into their prior knowledge framework by utilizing concept mapping. Furthermore, representation and organization of the knowledge through concept maps, helps retention and recall. Thus concept maps facilitate meaningful learning by organizing knowledge in cognitive structure and encourage creative thinking. Concept maps constructed by the teachers, enable students identify and explore the structure and the nature of knowledge. The use of concept maps can also assist teachers in evaluating the process of teaching. This study aims to investigate the elementary teachers’ views on concept maps by using an open-ended questionnaire which is carried out with 24 elementary teachers. Before conducting the questionnaire teachers have been instructed about concept maps and they constructed concept map examples. The findings indicate that elementary teachers generally perceive concept maps as a useful, effective, practical tool and they highlighted concept maps as important since they provide feedback. An important implication of this study is that there is a need for teachers to know how to teach concept map construction, to associate the concept maps into their lessons and into the evaluating process.