Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Searchability of Automatically Transcribed Lectures Through Dynamic Language Modelling

Recording university lectures through lecture capture systems is increasingly common. However, a single continuous audio recording is often unhelpful for users, who may wish to navigate quickly to a particular part of a lecture, or locate a specific lecture within a set of recordings. A transcript of the recording can enable faster navigation and searching. Automatic speech recognition (ASR) technologies may be used to create automated transcripts, to avoid the significant time and cost involved in manual transcription. Low accuracy of ASR-generated transcripts may however limit their usefulness. In particular, ASR systems optimized for general speech recognition may not recognize the many technical or discipline-specific words occurring in university lectures. To improve the usefulness of ASR transcripts for the purposes of information retrieval (search) and navigating within recordings, the lexicon and language model used by the ASR engine may be dynamically adapted for the topic of each lecture. A prototype is presented which uses the English Wikipedia as a semantically dense, large language corpus to generate a custom lexicon and language model for each lecture from a small set of keywords. Two strategies for extracting a topic-specific subset of Wikipedia articles are investigated: a naive crawler which follows all article links from a set of seed articles produced by a Wikipedia search from the initial keywords, and a refinement which follows only links to articles sufficiently similar to the parent article. Pair-wise article similarity is computed from a pre-computed vector space model of Wikipedia article term scores generated using latent semantic indexing. The CMU Sphinx4 ASR engine is used to generate transcripts from thirteen recorded lectures from Open Yale Courses, using the English HUB4 language model as a reference and the two topic-specific language models generated for each lecture from Wikipedia. Three standard metrics – Perplexity, Word Error Rate and Word Correct Rate – are used to evaluate the extent to which the adapted language models improve the searchability of the resulting transcripts, and in particular improve the recognition of specialist words. Ranked Word Correct Rate is proposed as a new metric better aligned with the goals of improving transcript searchability and specialist word recognition. Analysis of recognition performance shows that the language models derived using the similarity-based Wikipedia crawler outperform models created using the naive crawler, and that transcripts using similarity-based language models have better perplexity and Ranked Word Correct Rate scores than those created using the HUB4 language model, but worse Word Error Rates. It is concluded that English Wikipedia may successfully be used as a language resource for unsupervised topic adaptation of language models to improve recognition performance for better searchability of lecture recording transcripts, although possibly at the expense of other attributes such as readability.
Exfoliated and Restacked MoS2 and WS2: Ionic or Neutral Species? Encapsulation and Ordering of Hard Electropositive Cations

The relationship between charge and structure in restacked MS2 (M = Mo, W) has been probed by cation encapsulation and chemical oxidation and characterized by elemental analysis, electron diffraction, X-ray diffraction, and Differential Scanning Calorimetry. Alkali cations have been encapsulated in MoS2 and WS2 without the presence of a co-intercalated counterion, suggesting a negative charge in the 0.15−0.25 electrons per M atom range. Electron diffraction studies show ordering of these cations between the layers. Chemical oxidation with I2 or Br2 results in a change in the structure of restacked MoS2, giving rise to a a × a superlattice, whereas no change is observed in the structure of restacked WS2. Differential Scanning Calorimetry studies show that the irreversible exothermic transition to 2H-MS2 shifts to lower temperature with oxidation. The observed structural distortion and residual negative charge uniquely explain the thermopower measurements, which indicate that restacked MoS2 and WS2 are p-ty.
NoC Testbench Based on SystemVerilog

For solving the low efficiency of Network on Chip(NoC) verification,this paper constructs the coverage-driven constrained random and hierarchical NoC testbench based on the Verification Methodology Manual(VMM) and application of SystemVerilog.Results of NoC performance evaluation with heterogeneous topologies or traffic distributions show that the testbench is superior in generality,has good adaptability,scalability,and can effectively improves the verification efficiency.
QoS based Radio Resource Management Techniques for Next Generation MU-MIMO WLANs: A Survey

IEEE 802.11 based Wireless Local Area Networks (WLANs) have emerged as a popular candidate that offers Internet services for wireless users. The demand of data traffic is increasing every day due to the increase in the use of multimedia applications, such as digital audio, video, and online gaming. With the inclusion of Physical Layer (PHY) technologies, such as the OFDM and MIMO, the current 802.11ac WLANs are claiming Gigabit speeds. Hence, the existing Medium Access Control (MAC) must be in a suitable position to convert the offered PHY data rates for efficient throughput. Further, the integration of cellular networks with WLANs requires unique changes at MAC layer. It is highly required to preserve the Quality of Service (QoS) in these scenarios. Fundamentally, many QoS issues arise from the problem of effective Radio Resource Management (RRM). Although IEEE 802.11 has lifted PHY layer aspects, there is a necessity to investigate MAC layer issues, such as resource utilization, scheduling, admission control and congestion control. In this survey, a literature overview of these techniques, namely the resource allocation and scheduling algorithms are briefly discussed in connection with the QoS at MAC layer. Further, some anticipated enhancements proposed for Multi-User Multiple-Input and Multiple-Output (MU-MIMO) WLANs are discussed.
Mental Images And Their Transformations

Thank you very much for downloading mental images and their transformations. Maybe you have knowledge that, people have search numerous times for their chosen novels like this mental images and their transformations, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their computer. mental images and their transformations is available in our book collection an online access to it is set as public so you can download it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the mental images and their transformations is universally compatible with any devices to read.
Implementación de una red neuronal de convolución para el reconocimiento de poses en imágenes de rostros

Convolutional neural networks belong to a set of techniques grouped under deep learning, a branch of machine learning, which has proven successful in recent years in image and voice recording recognition tasks. This paper explores the use of deep convolutional neural networks in the recognition of horizontal poses outside the plane. We propose a convolutional neural network architecture based on OpenCV open source libraries for classification of images of human faces within seven default poses. We present in details the optimized design of our architecture and our learning strategy. The classifier trained on a set of 2600 images of sizes: 33 × 33, 41 × 41, 65 × 65 y 81 × 81, achive an recognition rate of 85%, higher than the 78% achieved with the Eigenfaces algorithm, with nearly the same execution time.
Goldrattâ€™s Thinking Process: Is There a Place for it in the Total Enterprise Simulation

Designers of business simulations attempt to achieve representational validity through the use of algorithms that mimic the business world (Feinstein & Cannon, 2002). This paper introduces the Eliyahu Goldrattâ€™s Theory of Constraint and Thinking Process as a means of modeling the decision making process. Both the Theory of Constraints and the Thinking Process are described and explained through the application of a simulated small business start up. Possible application of this theory to the business simulation is explored.
Ubiquitous interactive displays: magical experiences beyond the screen

Ubiquitous Interactive Displays are interfaces that extend interaction beyond traditional flat screens. This thesis presents a series of proof-of-concept systems exploring three interactive displays: the first part of this thesis explores interactive projective displays, where the use of projected light transforms and enhances physical objects in our environment. The second part of this thesis explores gestural displays, where traditional mobile devices such as our smartphones are equipped with depth sensors to enable input and output around a device. Finally, I introduce a new tactile display that imbues our physical spaces with a sense of touch in mid air without requiring the user to wear a physical device. These systems explore a future where interfaces are inherently everywhere, connecting our physical objects and spaces together through visual, gestural and tactile displays. I aim to demonstrate new technical innovations as well as compelling interactions with one ore more users and their physical environment. These new interactive displays enable novel experiences beyond flat screens that blurs the line between the physical and virtual world.
Enterprise modeling with the Joint Use of User Requirements Notation and UML

This chapter introduces the user requirements notation (URN) standardized formal methods and its joint use with unified modeling language (UML) in enterprise modeling. It argues that the joint use of URN and UML can enhance enterprise models and coevolve with enterprise engineering processes. URN combines goals and scenarios to help reasoning and to capture user requirements prior to detailed design. Furthermore, URN can be integrated partially or entirely into an existing business process modeling approach without replacing current ways of creating and analyzing models in order to be useful. Modeled in the UML, a URN model may be incorporated into the rest of a system’s UML design documentation, seamlessly linking the documentation for the requirements elicitation part of a project to the whole, and to be fully integrated with the rest of the design documentation for a software system. IDEA GROUP PUBLISHING This paper appears in the book, Enterprise Modeling and Computing with UML edited by Peter Rittgen © 2007, Idea Group Inc. 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com ITB13473
User attributes oriented RBAC model

In traditional RBAC model,relationship between users and roles is static.According to this disadvantage,a user properties oriented RBAC model is put forward.The attributes collection and constraints are added based on the original model.In this model,dynamic relationship is constructed between users and roles according user attributes,the model characteristics and constraints are mainly discussed.Finally,the realization process of the model access control is explained.Compared with the general RBAC model,this model can dynamically allocate roles based on user attributes.
The domain of supervisory processes and the temporal organisation of behaviour

The possibility that the supervisory system of Norman & Shallice (1986) can be fractionated into different subprocesses is discussed. It is argued that confronting a novel situation effectively requires a variety of different types of process. It is then argued that evidence of separability of different processes may be obtained by the observation of very low correlations across patients on more than one measure on each of which frontal patients show a performance deficit. Examples of this are provided by examining the Hayling sentence completion and the Brixton spatial anticipation tasks. Finally, differential localization of the subprocesses and hence the conclusion that they are separable is discussed with respect to the localization of monitoring and verification processes in memory.
Survey on Image Segmentation

The image segmentation is a key technology for image processing,also is a classical,difficult problem for reserachers.No method which is fit for all segmentation problems has been found and no criterion for judging it established since this research started.In this paper,a survey on image segmentation methods such as threshold segmentation,edge detection and region extraction is given,and some new methods appeared recently and some researches on segmentation evaluation criterions are introduced respectively and finally a developing direction of the imgage segmentation technology is pointed out.
Six Object Tracking Algorithms: A Comparative Study

Objectives: To compare five different objects tracking algorithms performance wise with the proposed algorithm and to find out the best one among them for tracking of an object in occlusion and Background clutter condition i.e. when background contains target features. Methods/Analysis: In the proposed algorithm, the object’s position is obtained by Mean Shift tracking and then the prediction of object’s position is done through Kalman Filter. The Proposed method has Kalman Filter which consists of an adaptive system matrix and adaptive process error covariance and measurement error covariance matrices respectively. Adaptive system matrix of Kalman Filter is getting updated online depending on the quality of observation by Mean Shift algorithm and adaptive process and measurement noise covariance matrices are getting updated according to the variation in Bhattacharya Coefficient respectively. Findings: Proposed algorithm has a maximum value (0.2177 and 0.4821) of tracking efficiency metric i.e. Bhattacharya Coefficient in both video dataset among all the algorithms and it is taking less execution time (0.002761 sec and 0.005431 sec) than other Kalman filter based tracking algorithms. Applications/Improvements: Proposed algorithm is able to track the target in occlusion and background variation condition with more efficiency and less execution time than rest of the algorithms.
THE IMPACT OF TEXT REPRESENTATION AND PREPROCESSING ON AUTHOR IDENTIFICATION

Author identification, one of the popular topics in text classification and natural language processing, basically aims to determine the author of a given text through various analyses. In the literature, different text representation approaches and use of preprocessing steps are considered for author identification problem. This paper aims to comprehensively examine the impact of text representation and preprocessing steps on author identification specifically for Turkish language. For this purpose, the contributions of all possible combinations of different text representation approaches, namely unigram and bigram, together with the preprocessing tasks, including stemming and stop-word removal, to the performance of author identification are investigated. For the experimental evaluation, a brand new dataset is constituted. Also, two different classification algorithms, namely Multinomial Naive Bayes and Sequential Minimal Optimization, are employed. The results of the experimental analysis reveal that using bigram features alone should be avoided. Besides, it is shown that stop-words should be kept inside the text while stemming can be preferred depending on the classification algorithm so that higher performance can be achieved for author identification.
Online Knowledge Sharing: Who, What and Where to Share

Online knowledge sharing has been getting popular. People browse Internet websites to get a wide range learning resources online, from purely academic to all sorts of life tips. Furthermore, recent empirical studies confirm the importance of online knowledge sharing through various forms of social interaction, such as interactive and multimedia websites, discussion forum, and online social networks. However, there is always a need to understand what actually users do online, in order to more accurately assess if those tasks are effective to knowledge sharing. Thus, the present study captures what online tasks Internet users will do and explore if there are differences among individual Internet users. Through an online survey, this study collected 1607 completed questionnaires. It was found that, from a scale between 1 (never use) and 10 (frequent and everyday use), browsing webpages (mean=9.339), receiving email (mean=9.100), browsing online news (mean=8.584), writing email (mean=7.793) and using instant messaging (mean=7.366) are among the top five online tasks reported. Significant gender differences existed: much higher in female are tasks on browsing online photo (female/male mean=6.951/6.544, p<0.01); browsing social media sites (female/male mean=6.587/6.401, p<0.01); photo upload (female/male mean=4.974/4.302, p<0.001) where much higher in male are tasks on browsing discussion forums (female/male mean=5.812/6.791, p<0.001); writing in discussion forums (female/male mean=3.400/4.372, p<0.001); playing online game (female/male mean=3.370/3.821, p<0.01); and audio upload (female/male mean=1.940/2.194, p<0.01). Explanations with respect to social sphere, formation and maintenance of interpersonal relationships are given in the discussion section.
Simple Certificate Enrolment Protocol

This document specifies the Simple Certificate Enrolment Protocol (SCEP), a PKI protocol that leverages existing technology by using CMS (formerly known as PKCS #7) and PKCS #10 over HTTP. SCEP is the evolution of the enrolment protocol sponsored by Cisco Systems, which enjoys wide support in both client and server implementations, as well as being relied upon by numerous other industry standards that work with certificates.
The Complexity of Input and How It Contributes to Adult Second Language Acquisition

Previous research has explored the efficacy of different types of second language (L2) training in fostering adult L2 development (e.g., Norris & Ortega, 2000; Morgan-Short, Steinhauer, Sanz, & Ullman, 2012). However, relatively little attention has been paid to the type of input (e.g., simple or complex) provided during training, even though some literature supports the idea that simple input is more advantageous at initial stages of L2 development. The current study addressed this issue by exploring how the type of L2 input in implicit training conditions affects initial adult L2 development in terms of both overall learning and the type of knowledge developed. Participants were assigned to training conditions where they received either simple or complex input during L2 training and learned an artificial L2 in order to play a computerized board game. After training, participants completed a grammaticality judgment task (GJT) that assessed grammar rule knowledge and a comprehension task to assess L2 development. Participants also responded to subjective measures that were embedded in the GJT (Rebuschat &Williams, 2012). Results showed better overall development on both the GJT and the comprehension test when learners were provided with simple input. Participants who received complex input showed above chance performance only on test items that paralleled the structure of training items. When examining knowledge development (through source attributions), learners in the simple input condition evidenced more diverse types of knowledge (both explicit and implicit) than learners in the complex input condition. These results suggest that providing adult L2 learners with simple input leads to greater overall development at the initial stages of learning an L2.
Open Problems In Communication And Computation

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New Ecotoxicologically and Biogenetically Relevant Terpenes of the tropical green seaweed Caulerpa taxifolia which is invading the Mediterranean

The tropical green seaweed Caulerpa taxifolia (VAHL) C. AGARDH (Caulerpales) which is invading the Mediterranean is shown to contain trace amounts of two further novel terpenes, 7,7-C-didehydro-6-hydroxy-6,7-dihydrocaulerpenyne (= (4S, 6S,1E)-3-[(Z)-acetoxymethylidene]-6-hydroxy-11-methyl-7-methylidenedodeca-1,10-dien-8-yne-1,4-diyl diacetate; 3a) and taxifolione (= 6-methylhept-5-en-3-yn-2-one; 4). The former is the most active of the toxins so far isolated from this seaweed, both as an in vitro inhibitor of the growth of marine bacteria and as a cytotoxic agent toward marine ciliate protists. This suggests a central ecotoxicological role for triacetate 3a as an adjuvant factor in the invasion of the Mediterranean by this seaweed. Moreover, the almost equally toxic 10,11 -epoxycaulerpenyne (2) which is scarcely available from Nature for bioassays can now be obtained by peroxy-acid epoxidation of caulerpenyne (1), along with the 6,7-epoxycaulerpenynes 6b and 6a. The latter are very labile, 6a giving triacetate 3a, suggesting epoxides to be late biogenetic intermediates in C. taxifolia.
Chapter 8. The third dimension

This chapter describes a theoretical framework for the design and evaluation of pedagogical tasks for 3D virtual world environments. The proposed framework is informed by Vygotskian Sociocultural Theory (SCT) and Activity Theory, two related sociocultural approaches to second (L2) language learning which, I argue, offer a particularly suitable paradigm for the design, implementation, and evaluation of technology-mediated tasks. Firstly, I provide an overview of what characterises 3D virtual worlds (3D VWs) and of current research into the potential of this technological application in the service of second language learning and teaching, and the range of tasks that this research has thus far inspected. Secondly, I briefly review core SCT concepts underlying the proposed framework and point out how they apply to 3D VW tasks. I then identify pedagogical principles derived from this approach to L2 learning and discuss their relevance in the context of technology-mediated task-based language teaching (TBLT) with specific reference to the current state and capabilities of 3D VWs. I also outline a task example designed to capitalise on the potential of 3D VWs for L2 learning. I conclude with a proposal for the application of Activity Theory to the evaluation of 3D VWs tasks. At a theoretical level, my goal in the chapter is to bring key sociocultural perspectives to TBLT and show how SCT can inform theoretically sound pedagogical design in TBLT. At a practical level, I hope to offer a framework for practitioners to support the design and evaluation of technology-mediated tasks in general and 3D VWs tasks in particular.
Stochastic Methods for Hard Optimization: Application to Robust Control and Fault Diagnosis of Industrial Systems

In all areas of engineering, physical and social sciences, one encounters problems involving the optimization of some objective function. Usually, the problem to solve can be formulated precisely but is often, difficult or impossible to solve either analytically or through conventional numerical procedures. This is the case when the problem is non-convex and so inherently nonlinear and multimodal. In fact it is now abStract