Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction and Optimization of Speech Intelligibility in Adverse Conditions

In digital speech-communication systems like mobile phones, public address systems and hearing aids, conveying the message is one of the most important goals. This can be challenging since the intelligibility of the speech may be harmed at various stages before, during and after the transmission process from sender to receiver. Causes which create such adverse conditions include background noise, an unreliable internet connection during a Skype conversation or a hearing impairment of the receiver. To overcome this, many speech-communication systems include speech processing algorithms to compensate for these signal degradations like noise reduction. To determine the effect on speech intelligibility of these signal processing based solutions, the speech signal has to be evaluated by means of a listening test with human listeners. However, such tests are costly and time consuming. As an alternative, reliable and fast machine-driven intelligibility predictors are of interest, since they might replace listening tests, at least in some stages of the algorithm development process. Two important issues exist with current intelligibility predictors. (1) Many of these methods cannot reliably predict the effect of more advanced nonlinear signal processing algorithms on speech intelligibility. (2) Typically, these measures are based on very complex auditory models or use average statistics of minutes of running speech, which makes it difficult on how to design new (real-time) speech processing solutions in an optimal manner given such a measure. To this end we propose several new measures which show good prediction results with the intelligibility of nonlinear processed speech. The newly proposed measures are of a low computational complexity and mathematically tractable which make them suitable for optimization of new signal processing solutions which aim for improving speech intelligibility.
Computer-based recognition of intertextuality within the Hebrew Bible

This research examines three approaches to recognize intertextuality. Two of them are novel because of their involving of the special features. The first approach uses multiple distance metrics. These distance metrics measures the similarity between strings. The second approach uses high-level grammatical features. These features are based on grammatical characteristics of the text. The third approach involves the scale of language. Each sentence can be divided into lower scales, first into clauses, then into phrases and finally into words. This approach measures the distance of texts on these scales to find the exact intertextuality.
Automated Planning and Scheduling for Space Mission Operations

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.
Feature Extraction and Classification Technique in Neural Network

Feature extraction is the heart of an object recognition system. In recognition problem, features are utilized to classify one class of object from another. The original data is usually of high dimensionality. The objective of the feature extraction is to classify the object, and further to reduce the dimensionality of the measurement space to a space suitable for the application of object classification techniques. In the feature extraction process, only the salient features necessary for the recognition process are retained such that the classification can be implemented on a vastly reduced feature set. In paper we are going to discuss the feature as well as classification technique used in neural network.
Adaptive Processing of Brain Signals

In this book, the field of adaptive learning and processing is extended to arguably one of its most important contexts which is the understanding and analysis of brain signals. No attempt is made to comment on physiological aspects of brain activity; instead, signal processing methods are developed and used to assist clinical findings. Recent developments in detection, estimation and separation of diagnostic cues from different modality neuroimaging systems are discussed.
I/O brush

We introduce I/O Brush, a new drawing tool aimed at young children, ages four and up, to explore colors, textures, and movements found in everyday materials by “picking up” and drawing with them. I/O Brush looks like a regular physical paintbrush but has a small video camera with lights and touch sensors embedded inside. Outside of the drawing canvas, the brush can pick up color, texture, and movement of a brushed surface. On the canvas, children can draw with the special “ink” they just picked up from their immediate environment. In our preliminary study with kindergarteners, we found that children not only produced complex works of art using I/O Brush, but they also engaged in explicit talk about patterns and features available in their environment. I/O Brush invites children to explore the transformation from concrete and familiar raw material into abstract concepts about patterns of colors, textures and movements.
The Interplay of Firsthand and Text-Based Investigations in Science Education. Ciera Report.

This paper presents the results of a study concerning the use of text in support of firsthand scientific inquiry instruction in the early elementary grades. A partial transcript of two teaching sessions in which an expert classroom teacher incorporated text into her inquiry instruction is investigated. The knowledge gained from these sessions helped inform the development of a new text genre modeled on a scientist's notebook. Unlike traditional texts that simply present a body of information, the notebook format models the use of scientific reasoning for children. Sections include: (1) "The Interplay of Firsthand and Text-Based Investigations in Science Education"; (2) "What Is Known about Text in Science? "; (3) "The Professional Development Context Supporting This Program of Research"; (4) "Descriptive Research on Secondhand Investigations"; (5) "Designing Text To Support Guided Inquiry Teaching"; (6) "Experimental Research Comparing the Innovative Text with Traditional Text"; (7) "Results and Discussion"; and (8) "Observational Research with the Innovative Text. " (CCM) Reproductions supplied by EDRS are the best that can be made from the original document.
Spatial auditory display for acoustics and music collections

This thesis explores how audio can be better incorporated into how people access information and does so by developing approaches for creating three-dimensional audio environments with low processing demands. This is done by investigating three research questions. Mobile applications have processor and memory requirements that restrict the number of concurrent static or moving sound sources that can be rendered with binaural audio. Is there a more efficient approach that is as perceptually accurate as the traditional method? This thesis concludes that virtual Ambisonics is an efficient and accurate means to render a binaural auditory display consisting of noise signals placed on the horizontal plane without head tracking. Virtual Ambisonics is then more efficient than convolution of HRTFs if more than two sound sources are concurrently rendered or if movement of the sources or head tracking is implemented. Complex acoustics models require significant amounts of memory and processing. If the memory and processor loads for a model are too large for a particular device, that model cannot be interactive in real-time. What steps can be taken to allow a complex room model to be interactive by using less memory and decreasing the computational load? This thesis presents a new reverberation model based on hybrid reverberation which uses a collection of B-format IRs. A new metric for determining the mixing time of a room is developed and interpolation between early reflections is investigated. Though hybrid reverberation typically uses a recursive filter such as a FDN for the late reverberation, an average late reverberation tail is instead synthesised for convolution reverberation. Commercial interfaces for music search and discovery use little aural information even though the information being sought is audio. How can audio be used in interfaces for music search and discovery? This thesis looks at 20 interfaces and determines that several themes emerge from past interfaces. These include using a two or three-dimensional space to explore a music collection, allowing concurrent playback of multiple sources, and tools such as auras to control how much information is presented. A new interface, the amblr, is developed because virtual two-dimensional spaces populated by music have been a common approach, but not yet a perfected one. The amblr is also interpreted as an art installation which was visited by approximately 1000 people over 5 days. The installation maps the virtual space created by the amblr to a physical space.
Gene Interaction Analysis Using k-way Interaction Loglinear Model: A Case Study on Yeast Data

Microarray data provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that show similar expression patterns. However, this approach usually fails to unveil multiple interactions by the same gene. Association rule mining has been used for this purpose, but the inherent limitations of association rules limit the applicability of the results. In this paper we use a combination of association rule mining and loglinear modeling to discover k-gene interactions. Using this technique we can discover interactions among k-genes that cannot be explained by the combined effects of any of the subsets of those genes. We test our technique experimentally, using yeast microarray data. Our results reveal some previously unknown associations that have solid biological explanations.
A Sound and Complete Distributed Algorithm for Distributed Commerce Transactions

In situations where self-interested agents are interacting in an environment of distrust, commercial exchanges may be blocked due to a lack of trust. We propose a fully distributed algorithm that each agent may run to provide minimum guarantees about the outcomes of such exchanges. The algorithm is shown in operation on two examples, one feasible and one not, and is proven to be sound and complete. The algorithm is extended to consider situations in which direct trust does exist between certain participants and those with deadlines for completion. Examples and proofs of soundness and completeness are given for these extensions as well.
Sensing the Natural in the Caribbean's Nature Island

ABSTRACT This article uses research carried out in the Caribbean island of Dominica to consider how sensory experiences shape and influence people's perceptions of and relationships to nature. People's ideas of nature are not purely abstract; they are embodied and emplaced in geographical and social contexts. That is, people acquire understandings of nature through their experiences of the natural world, their engagements with flowers and birds, rivers and mountains, forests and vegetable gardens. On this basis, this article explores how sensory perception, in addition to being a way to apprehend the material reality of the natural environment, also plays a role in how people relate to and think about nature and the natural, based on their bodily experiences in a particular place.
Kooperation und Kommunikation in heterogenen Rechner- und Sprachumgebungen mit Perl-Linda

Diese Arbeit stellt Perl-Linda, einen flexiblen Prototyp fur die Implementation des Koordinations- und Kommunikationsmodells Linda fur ein Netzwerk von Workstations vor. Der Autor zeigt zuerst Trends in der Informationstechnologie auf, insbesondere die globale Vernetzung durch das Internet, die eine Anderung der Anforderungen an Applikationen herbeifuhren. Durch die immer weitere Verbreitung des Betriebsystems UNIX stellen Netzwerke von UNIX-Workstations eine preisgunstige und in einer Vielzahl von Organisationen verfugbare Variante zu Super- und Parallelrechnern dar. Aufbauend auf den bereits zu Linda existierenden Arbeiten und Implementationen, wird Perl-Linda, ein Prototyp geschaffen, der auf Client/Server-Basis eine einheitliche Schnittstelle fur die Erweiterung von Programmiersprachen um den Linda-Befehlssatz implementiert. Auf Basis dieser Schnittstelle werden die fur einige Programmiersprachen wie C, C++, Perl und APL, erstellten Client-APIs beschrieben und deren Funktion anhand von Beispielen erlautert. Die Entwicklungsschritte zum Design und zur Entwicklung einer Linda-Applikation werden beschrieben und an Beispielen durchgefuhrt. Abschliesend wird der Einsatz von Linda fur die Erweiterung der Funktionalitat des World Wide Web-Systems (WWW) fur die Schaffung von WWW-basierten Transaktionssystemen gezeigt. Es werden mit Linda und WWWrealisierte Informationssysteme als Beispielapplikationen vorgestellt und erlautert. (Autorenref.)
Analysis of Free-Form Battlefield Reports with Shallow Parsing Techniques

Abstract : A natural way to communicate with C2 systems would be to use natural language. Natural language components are already used in military systems, for example, CommandTalk is a spoken-language interface to the ModSAF battlefield simulator. In project SOKRATES, the authors use shallow parsing techniques for written language to analyze German free-form battlefield reports. These reports are processed by transducers. The extraction result is formalized in feature structures, semantically enriched by the semantic analysis, and the augmented result is then stored in the ATCCIS database. After storage in the database, triggers initiate a change in the position of a tactical symbol on the tactical map. Shallow parsing techniques are the basis for information extraction. In this paper, the authors first introduce the promising field of information extraction, and then describe in detail how shallow parsing techniques are used in project SOKRATES. Twenty-four briefing charts summarize the presentation. (2 figures, 15 refs.)
An Evaluation of Electronic Annotated Readers for First Graders in Chinese Dual Immersion to Improve Reading Comprehension and Character Recognition

An Evaluation of Online Annotated Readers Designed to Improve Chinese Character Comprehension for First Grade Students Enrolled in Early Chinese Language Immersion James H. Cloe, Jr. Center for Language Studies, BYU Master of Arts of Language Acquisition and Teaching This study is an evaluation of online, annotated readers developed for first grade students enrolled in Chinese immersion. The electronic readers were created to provide additional input to immersion students, who had little time in class for Chinese character reinforcement. The students accessed online readers from their homes and took assessments before and after each reader to test for improved character comprehension. In addition, students were divided into treatment and control groups. The treatment group had annotated electronic readers with audio and games. Conversely, the control group did not have annotations but audio was included. Results demonstrate a significant difference between preliminary and post-assessments, suggesting that students comprehended more characters after reading. No significant differences were detected between the control (non-annotated) and treatment (annotated) groups. Additional data collected from parent surveys provide useful demographics about subjects’ socio-cultural and language variables as well as highlight parental desires for more support and help-aides. Computer Assisted Language Learning (CALL) in relationship to young immersion students learning Chinese is also discussed. Results suggest that online, annotated readers can be an important resource for students who have limited instructional time in the classroom and little opportunity to receive help at home.
Reinforcement learning for continuous action using stochastic gradient ascent

This paper considers a reinforcement learning (RL) where the set of possible action is continuous and reward is considerably delayed. The proposed method is based on a stochastic gradient ascent with respect to the policy parameter space; it does not require a model of the environment to be given or learned, it does not need to approximate the value function explicitly, and it is incremental, requiring only a constant amount of computation per step. We demonstrate the behavior through a simple linear regulator problem and a cart-pole control problem.
Induced Amnesia for Distressing Information in a Nonclinical Sample

Abstract Dissociative reactions during and subsequent to traumatic events are theorised to result in memory deficits for trauma-related information. This study investigated the interaction between induced amnesia and dissociative reactions. Participants (N = 29) were presented with a word list, a series of disfigured or neutral faces and a second word list, followed by free recall and recognition tasks. Participants presented with disfigured faces recalled fewer words from the postimage list in the free recall task than those presented with neutral faces; however, there were no between-group differences for recognition. No relationship was observed between dissociative tendencies and memory performance. Trait dissociation was unrelated to induced amnesia effects. Findings are interpreted in terms of impaired consolidation of information following encoding of distressing information. Implications of the results for the clinical management of traumatized individuals are considered.
Impact of Site Characteristics on Recommendation Models Based On Association Rules and Sequential Patterns

A number of studies have suggested the use of discovered Web usage patterns such as association rules, general sequential patterns, and contiguous sequential patterns (frequent navigational paths) for generating recommendations in personalization systems. To-date, however, no studies have considered the conditions under which recommendation models based on sequential patterns may be more appropriate for personalization as compared to those based on non-sequential patterns (such as frequent itemsets). We conjecture that the structural characteristics of Web sites, such as the site topology and the degree of connectivity, have a significant impact on the relative performance of these recommendation models. We present a framework forWeb personalization based on association rules, contiguous and non-contiguous sequential patterns discovered from Web usage data. We then conduct a detailed comparative evaluation based on real Web usage data from three sites with different structural characteristics. Our results suggest that less constrained patterns, such as frequent itemsets, are better suited for personalization in sites with a higher degree of connectivity and shorter navigational depth, while the sequential recommendation models may be more suitable in sites with deeper navigational depth or in sites relying on many dynamically generated pages.
Digital Video Broadcasting (DVB); Implementation guidelines for DVB terrestrial services; Transmission aspects

The present document may be made available in more than one electronic version or in print. In any case of existing or perceived difference in contents between such versions, the reference version is the Portable Document Format (PDF). In case of dispute, the reference shall be the printing on ETSI printers of the PDF version kept on a specific network drive within ETSI Secretariat. No part may be reproduced except as authorized by written permission. The copyright and the foregoing restriction extend to reproduction in all media.
The Feasibility of Implementing a Collaborative Recommender System for the Brigham Young University Harold B. Lee Library

With library users finding their information from other non-library sources, the Harold B. Lee Library at Brigham Young University has great need of a recommender system. The library already has years of checkout data that can be used to jump-start the recommender system's recommendations. Unfortunately, that data is difficult to format in a way that a recommender system can use. With some effort, it can be stored in a graph database and used to generate recommendations for users based on their preferences. Calculating recommendations before they are required and storing them for future use can speed up the amount of time it takes the recommender system to retrieve recommendations.
Error Classification and Reduction in Solid State Qubits

Quantum computers have enormous advantages over classical computers. A quantum computer can be used to calculate the factors of a number, which is sometimes impossible during one’s lifetime with a classical computer. Quantum information processing techniques can also be used for encryption, which makes eavesdropping impossible. Noise from the environment is a great challenge in building a reliable quantum computer. To build a reliable quantum computer, one has to protect the information content of the system from the environment. Otherwise, the information associated with the system will decay as the system interacts with the environment. The noise resulting from the system-bath interaction can be removed by using quantum error correcting codes or decoupling pulses. In addition, one could also use DFS encoding to make the information content of the system immune to the noise. In this paper, the various types of errors that could arise in a specific DFS encoding of a 3 spin qubit have been classified according to their effect on the state of the qubit. Also, the application of a specific decoupling pulse on the system, which is coupled to the environment through hyperfine Hamiltonian, has
Surface matching for correlation of virtual models: Theory and application

Virtual reality can enable a robot user to off line generate and test in a virtual environment a sequence of operations to be executed by the robot in an assembly cell. Virtual models of objects are to be correlated to the real entities they represent by means of a suitable transformation. A solution to the correlation problem, which is basically a problem of 3-dimensional adjusting, has been found exploiting the surface matching theory. An iterative algorithm has been developed, which matches the geometric surface representing the shape of the virtual model of an object, with a set of points measured on the surface in the real world. A peculiar feature of the algorithm is to work also if there is no one-to-one correspondence between the measured points and those representing the surface model. Furthermore the problem of avoiding convergence to local minima is solved, by defining a starting point of states ensuring convergence to the global minimum. The developed algorithm has been tested by simulation. Finally, this paper proposes a specific application, i.e., correlating a robot cell, equipped for biomedical use with its virtual representation.