Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixed-Frequency Modeling and Economic Forecasting

Economic downturn and recession that many countries experienced in the wake of the global financial crisis demonstrate how important but difficult it is to forecast macroeconomic fluctuations, especially within a short time horizon. The doctoral dissertation studies, analyses and develops models for economic growth forecasting. The set of information coming from economic activity is vast and disparate. In fact, time series coming from real and financial economy do not have the same characteristics, both in terms of sampling frequency and predictive power. Therefore short-term forecasting models should both allow the use of mixed-frequency data and parsimony. The first chapter is dedicated to time series econometrics within a mixed-frequency framework. The second chapter contains two empirical works that sheds light on macro-financial linkages by assessing the leading role of the daily financial volatility in macroeconomic prediction during the Great Recession. The third chapter extends mixed-frequency model into a Bayesian framework and presents an empirical study using a stochastic volatility augmented mixed data sampling model. The fourth chapter focuses on variable selection techniques in mixed-frequency models for short-term forecasting. We address the selection issue by developing mixed-frequency-based dimension reduction techniques in a cross-validation procedure that allows automatic in-sample selection based on recent forecasting performances. Our model succeeds in constructing an objective variable selection with broad applicability.
Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties

This volume contains the papers accepted for presentation at the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties. The workshop is endorsed by the Association for Computational Linguistics Special Interest Group on the Lexicon (SIGLEX) and is hosted in conjunction with the COLING/ACL 2006 on July 23rd, 2006 in Sydney, Australia. There has been a growing awareness in the NLP community of the problems that multiword expressions (MWEs) pose. Developments in areas such as machine translation, text summarization, paraphrasing, grammar development and parsing, information retrieval, and question answering (to mention a few) have acknowledged difficulties due to the idiosyncratic nature of multiword expressions. This workshop continues a tradition of ACL workshops on Collocations (2001) and Multiword Expressions (2003 and 2004). Its specific objective is to focus on the underlying properties of MWEs. The call for papers expressed our interest in several topics such as the definition of MWEs, properties of MWEs and their impact on NLP applications, representation and treatment of the different classes of MWEs, linguistic and psycholinguistic analyses of MWEs, evaluation of extraction techniques and the importance of (non-)compositionality. We received 23 submissions in total. Each submission was reviewed by (at least) three members of the program committee who not only judged each submission but also gave detailed comments to the authors. Among the received papers, 10 were selected for presentation at the workshop. After 3 papers have been withdrawn by their authors, seven papers are included in these proceedings. The intention of this workshop is to focus on some fundamental questions on the nature of MWEs. To do this we will allow plenty of time for discussion to pursue some of the interesting, open and difficult questions that MWEs raise. As well as a discussion period after each session of papers, we will be organising group discussions at the end of the workshop. These will focus on problems of defining, characterising and evaluating MWEs, given what we know about the range of phenomena that they encompass as well as any important questions that have arisen during the workshop.
A new classification rule based on nearest neighbour search

The nearest neighbour (NN) classification rule is usually chosen in a large number of pattern recognition systems due to its simplicity and good properties. As the problem of finding the nearest neighbour of an unknown sample is also of interest in other scientific communities (very large databases, data mining, computational geometry), a vast number of fast nearest neighbour search algorithms have been developed during the last years. In order to improve classification rates, the k-NN rule is often used instead of the NN rule, but it yields higher classification times. In this work we introduce a new classification rule applicable to many of those algorithms in order to obtain classification rates better than those of the nearest neighbour (similar to those of the k-NN rule) without significantly increasing classification time.
Toward a Taxonomy Linking Game Attributes to Learning

The serious games community is moving toward research focusing on direct comparisons between learning outcomes of serious games and those of more traditional training methods. Such comparisons are difficult, however, due to the lack of a consistent taxonomy of game attributes for serious games. Without a clear understanding of what truly constitutes a game, scientific inquiry will continue to reveal inconsistent findings, making it hard to provide practitioners with guidance as to the most important attribute(s) for desired training outcomes. This article presents a game attribute taxonomy derived from a comprehensive literature review and subsequent card sorts performed by subject matter experts (SMEs). The categories of serious game attributes that emerged represent the shared mental models of game SMEs and serve to provide a comprehensive collection of game attributes. In order to guide future serious games research, the existing literature base is organized around the framework of this taxonomy.
A Comprehensive Review of Cloud Computing Simulators

Cloud Computing is an innovation idea that has enabled the organizations to access high performance computing and storage infrastructure at reduced cost through internet. Cloud computing is model in which customer can access IT resources which are priced and provided on demand. Cloud Service providers charge user depending upon space or whatever service availed. It is not always possible for researchers and academicians to have the actual cloud infrastructure for performing experiments, executing or implementing their algorithms. To fulfill their need for the purpose of testing and actual providing them a feel of cloud services simulators are required. Nowadays cloud simulators are widely available in the market for researcher scholars. The objective of this research paper is to do comprehensive review of cloud computing simulators and to research out to get the best cloud computing simulation tool for security based research in area of Cloud.
Distributed Diagnosis of Networked, Embedded Systems

Abstract : Networked embedded systems are composed of a large number of physically distributed nodes that interact with the physical world via a set of sensors and actuators, have their own computational capabilities, and communicate with each other via a wired or wireless network. Monitoring and diagnosis for such systems must address several challenges caused by the distribution of resources, communication limitations, and node and link failures. This paper presents a distributed diagnosis framework that exploits the topology of a physical system to be diagnosed to limit inter-diagnoser communication and compute diagnoses in an anytime and any information manner, making it robust to communication and processor failures. The framework adopts the consistency-based diagnosis formalism and develops a distributed constraint satisfaction realization of the diagnosis algorithm. Each local diagnoser first computes locally consistent diagnoses, taking into account local sensing information only. The local diagnosis sets are reduced to globally consistent diagnoses through pairwise communications between local diagnosers. The algorithm has been successfully demonstrated for the diagnosis of paper path faults for the Xeros DC265 printer.
A Method for Computing Unsteady Flows in Porous Media

This volume is self-contained and concise, providing a basis to study unsteady flow in saturated porous media. It provides for the development of algorithms that examine three-dimensional flows subject to complicated boundary conditions that are a natural consequence of flow in geological systems. A new way to understand flow in porous media is presented. The authors pay close attention to computational considerations, and options for developing codes are addressed. Chapter topics include general theory, the initial-boundary-value problem, treatment of extraction points, computational considerations, flow in fissured and layered porous media. The volume includes a glossary, an appendix covering fundamental solution for slab reservoirs, and index.
VLSI implementation of neural networks

One of the main contributions to the resurgence of interest in artificial neural networks in the early 80's was the work of Hopfield (1982) on feedback architectures with nonlinear threshold elements. Since the development of VLSI devices for the implementation of neural networks was initially stimulated by this work, the principles behind the Hopfield model are reviewed briefly. The paper then discusses: general principles of VLSI implementation, analogue VLSI neural networks, and pulse-stream VLSI neural networks. >
Performance Comparison of PWM Methods for 27-Level Hybrid Multilevel Inverters

Multilevel inverters have become more popular due to reduced switching losses, low costs, low harmonic distortion and high-voltage capability when compared to traditional PWM inverters. A new family of multilevel inverters that has decreased the number of separated DC sources has emerged named as hybrid multilevel inverter. In this study, theories and applications of four PWM modulation methods for 27 level hybrid multilevel inverters are examined. The comparative case studies are presented to validate the examined modulation technique through harmonic spectrum analysis, output voltage magnitude, THD, WTHD and simulation using Power System Computer Aided Design Program (PSCAD). Key Words : Hybrid multilevel inverters, H-bridge inverters, Reference signal generation, Pulse width modulation (PWM).
Investigating the Use of Learning Objects for Secondary School Mathematics

Research on the impact of learning objects in secondary school mathematics classes is limited. To date, only two investigations have been reported in this area. The current study presents a comprehensive analysis of the use and effect of learning objects in secondary school mathematics classrooms. T eacher and student attitudes, as well as student performance, were used to assess the impact of learning objects for 298 students and 11 teachers in 20 different classrooms. T eacher attitudes were positive with respect to quality, engagement, and learning value of learning objects. Student attitudes, on the other hand, varied markedly. Overall, student performance increased significantly after using learning objects, although gains observed were small and highly variable. Student performance was significantly related to the intended purpose of a lesson and teaching strategy selected. Planning time, using learning objects for review or to introduce new concepts, and supplying guided handouts improved student performance. It is reasonable to conclude that mathematics-based learning objects are viable teaching tools when used with the appropriate goals and strategies. Ke ywords: mathematics, use, evaluate, secondary school, learning object
Linked Task Scheduling : Algorithms for the Single Machine Case

We consider a system made of one resource. The execution of the tasks is non-preemptive on this resource. The tasks we consider are composed of a given number of subtasks, two consecutives subtasks being separated by an idle period. These idle periods may be used for executing other subtasks. We wish to insert a new task in a given schedule. The characteristics of this task are not known before it appears, and its execution must be completed before a given deadline. The criterion is the minimization of the increase of the sum of the delays of the tasks.
Concurrent hardware : the theory and practice of self-timed design

The Models of Parallel Processes Specification and the Behaviour of the Circuits Verification of Parallel System Behaviour Through Formal Models The Relationship between the State and Event Models Behaviour Identification and Circuit Analysis Transformation of the Behaviour Specifications Language Meccano Methods for Direct Translation of Specification into Circuits Formal Methods for Self-Timed Circuit Synthesis Reducing Specification to the Form Implementable Through Circuits Abridged Review of the State of the Art in Self-Timing Use of the CAD System 'FORCAGE' in the Design of Self-Timed Circuits.
Perspectives in process analysis

Process analysis is a transdisciplinary technology. Process chemists, process engineers, chemometricians, and many other technologists must work together and put more emphasis on the essentials of science of each discipline. This perspective analyzes potential strategies for intelligent production in the future. It emphasizes the need for a holistic approach where multimodality will be a bedrock supporting the production of smart materials in smart factories. Copyright © 2013 John Wiley & Sons, Ltd.
Some Component Generation Approaches for E-Governance Systems

E-governance is a plan for the national interest and in order to meet its objectives within the given timescale, more and more applications, or at least some of their modules, must be reusable by other software. It is possible to reuse the solutions developed for one government, by another government. What is required at this stage is a move from more traditional software development to a reuse based development. Component-Based Development (CBD), an approach to develop a software system with the assistance of reusable software components, may help to reduce the development time and costs and will increase reliability and maintainability of such systems. This paper suggests some component development approaches for developing software components that can be reused in component based E-governance software systems. The proposed methodologies can be used as a reference model for the development of software components for E-governance solutions.
Author Profiling: Predicting Gender and Age from Blogs, Reviews & Social Media

Author profiling aims to determine the gender, age, and mother language, level of education or socio-economic categories of authors by analyzing their published texts. In the recent times, several solutions are being proposed by different researchers focusing primarily on Age and Gender prediction of the authors. In this paper, we propose a Machine Learning approach to determine authors Age and Gender. Our approach uses two types of features: Content based and Style based. In content based features, we considered the words used by authors, in style based features we have considered parts of speech taggers of the words. We evaluated our system using PAN 2014 author profiling dataset on Blogs, Reviews and Social Media data.
Application of hidden Markov models for recognition of a limited set of words in unconstrained speech

The authors present an algorithm based on hidden Markov models which can recognize a predefined set of vocabulary items spoken in the context of fluent speech. They show that for a vocabulary of five words, it is possible to correctly recognize 87.1% of keywords when they occur in fluent speech and are spoken over a long-distance telephone network. While this task is significantly easier than what is normally associated with keyword spotting in continuous speech, it does address an important problem that must be solved for successful deployment of speech-recognition technology. <<ETX>>
Formal methods in human-computer interaction

Preface Contributors 1. The role of formal methods in human-computer interaction Michael Harrison and Harold Thimbleby 2. HCI formalisms and cognitive psychology: the case of Task-Action Grammar Franz Schiele and Thomas Green 3. Putting design into practice: formal specification and the user interface Roger Took 4. Non-determinism as a paradigm for understanding the user interface Alan Dix 5. A state model of direct manipulation in interactive systems Michael Harrison and Alan Dix 6. Specification, analysis and refinement of interactive processes Bernard Sufrin and Jifeng He 7. From abstract models to functional prototypes Colin Runciman 8. Designing abstractions for communication control Gilbert Cockton 9. Structuring dialogues using CSP Heather Alexander Bibliography Index.
Corneal endothelium analysis by means of Bayesian shape modeling

A new method is proposed for the automatic detection of cell contour in images of corneal endothelium. The main drawback of the systems proposed so far in the literature, which mainly rely on classical image segmentation techniques, is the impossibility to embed prior information on the object being segmented, i.e., the regular hexagon pattern of endothelial cells. In our approach, the introduction and use of a-priori information is obtained by means of the Bayesian modelling framework, which allows to combine prior information on the applied model with experimental data through a statistical description of the model given the data. The resulting posterior probability density function is then optimized by a maximum a posteriori (MAP) estimator, using the simulated annealing maximization algorithm. Preliminary results on a few images showed that the developed system is capable of correctly recognizing the contour of cells. The developed theoretical framework is extremely flexible and can be easily adapted to different prior distributions or even to different object detection applications involving shape prior information.
Birkbeck Word Association Norms

This reference work contains free association norms for over 2000 words in the English language, collected over the last eight years from groups of 40-50 British English speakers between the ages of 17 and 45. These norms should be of use to researchers and students in many fields of psychology, especially the study of language and memory, where the degree of association between pairs of words is often an important experimental variable. The main part of the book contains an alphabetical list of all associative responses and their frequency for each of the 2464 stimulus words. In addition, there is an index of stimulus words organized according to semantic category to aid selection of experimental materials. Full methodological details of the collection and compilation of the data are also provided in the introduction.
Complexity Theory and Project Management: Curlee/Complexity

Preface. Acknowledgements. Introduction. Part I Complexity Theory. A Practitioner's Explanation of Complexity Theory. 1 Introduction to Complexity Theory. 2 Going beyond the Project Management Body of Knowledge (PMBOK) Guide. 3 Virtual Leadership and Complexity. 4 Successful Virtual Projects. Part II How to Deploy Complexity Theory. 5 Successful Project Management Strategies of Complexity. 6 Virtual Leadership through Complexity. 7 How Organizational Culture Is the Key to Applying Complexity. 8 Cultural Conflict through the Lens of Complexity. 9 Cultural Conflict Resolution Strategies. 10 Risk Management through the Lens of Complexity. Part III Case Studies of Applied Complexity. 11 SEMCO (Organizational Complexity). 12 Web-Based Universities (Multilevel Complexity). 13 Small Team Complexity. Part IV Create Successful Project Communities. 14 Leadership of Complexity-Driven Organizations. 15 Communities. 16 Teams and Complexity. 17 Micro-Teams (Tribes). 18 Dealing Appropriately with Change. Part V Advanced Tools for Managing Complexity. 19 Complexity Tools for Organizations with Virtual Teams. 20 Virtual Projects and Complexity Theory. 21 Using Complexity to Address a Troubled Project. 22 The Future of Complexity. Index.
A services-oriented architecture applied to artificial neural network

In this work, a services-oriented architecture that allows the utilization of artificial neural network models, through the Internet, is proposed. The Web Services, the Message Queuing and the Neural Network Markup Language constitute the technology used for the development of this approach. The module called by Artificial Neural Network-Web Service is the main module of the proposed architecture. It is an independent module, that accepts as entrance a description of the ANN characteristics and the necessary data to its training in a neural network markup language format returning as result the trained ANN. A main advantage of this approach is that any user can invoke this application programmatically over the Internet, without that it needs to have a computer with great capacity of processing.
Early evaluation of direct large-scale InfiniBand networks with adaptive routing

We assess the problem of choosing optimal direct topology for InfiniBand networks in terms of performance. Newest topologies like Dragonfly, Flattened butterfly and Slim Fly are considered, as well as standard Tori and Hypercubes. We consider some reasonable extensions to InfiniBand hardware which could be implemented by vendors easily and may allow reasonable routing algorithms for such topologies. A number of routing algorithms are proposed and compared for various traffic patterns. Mapping algorithms for Dragonfly and Flattened Butterfly are proposed. Based on this research it has been decided to use Flattened Butterfly topology for system #22 in November 2014 Top 500 list.
The Cortex of the Rat: A Stereotaxic Atlas

Nomenclature. - Coronal, Horizontal, and Sagittal Sections in Stereotaxic Coordinates. - Cortical Maps in Stereotaxic Coordinates. - Frontal and Caudal Aspects of the Hemisphere in Computer Reconstructions. - Delineation of Cortical Areas in Nissl- and Myelin-Stained Sections. - Laminar Structure of Cortical Areas in the Nissl- and Myelin-Stained Sections. - Aspects of Cortical Variability. - Index of Structures. - References and Further Reading. - Abbreviations: Folder at end of book.
Adoption of Web 2.0 technologies in education for health professionals in the UK: Where are we and why?

This paper describes the findings about the use of Web 2.0 technologies in the education of health professionals in the United Kingdom (UK). The work is part of a wider study scoping the use of e-learning. Its objectives were to: Explore issues influencing implementation and use by both early and late adopters Identify barriers to implementation and good practice Review the employment of e-learning within curricula representing a range of teaching models In phase one, a postal survey obtained data from 25 higher education institutions relating to their uptake and development in this field. A second phase identified four case studies, two from early and two late adopters, reflecting the features identified from phase one. In the case studies, interviews and focus groups with students and staff were conducted to gain a deeper understanding of the issues which were significant to them. The main findings suggested e-learning development and use varies, with a spectrum of employment across the sector. The predominant engagement is with instructivist learning approaches managed through a Virtual Learning Environment with only limited experimentation in interactive learning online. This paper will discuss the findings from the study where they relate to the limited use of Web 2.0 technologies. It will include a discussion on the moral, legal and ethical implications of current and future developments.