Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel microstrip low-pass/high-pass directional couplers/filters

The design of novel microstrip low-pass/high-pass couplers/filters is presented. The design is based on the equivalence principle of nonuniform transmission line directional couplers and the design procedure basically involves the determination of a realizable coupling coefficient function in the design bandwidth. The coupling coefficient distribution function is modified to obtain the necessary characteristics. This novel design offers the following features: if low-pass output is obtained from the coupled output, then the high-pass output is obtained from the direct output; and if high-pass output is obtained from the coupled output, then the low-pass output (from DC) is obtained from the direct output. The predicted performances with couplers that have dimensions within practical manufacturing limits are excellent. The unique feature of this novel design technique is the ability to obtain both low-pass and high-pass filter characteristics from a single component. <<ETX>>
Radiative transfer in the surfaces of atmosphereless bodies. I. Theory.

A generalized theory of radiative transfer is presented which includes single and multiple scattering of light in particulate surfaces, and is applicable to both the surfaces of atmosphereless bodies and to laboratory samples. Single scattering is described in terms of the effects of porosity and roughness, and is formulated by means of a probabilistic method. It is shown that, for low-albedo surfaces, the effects of porosity and roughness are separable, the opposition effect is caused by the former, and the slope of the linear part of the phase curve is mainly controlled by the latter. The theory, which is applicable to all albedos and phase angles, may be used in both surface brightness and integrated brightness studies. The limiting case of roughness and volume density tending to zero yields the results of classical radiative transfer theory.
Ponder: A Language for Specifying Security and Management Policies for Distributed Systems

This document defines a declarative, object-oriented language for specifying policies for the security and management of distributed systems. The language includes constructs for specifying the following basic policy types: authorisation policies that define permitted actions; event-triggered obligation policies that define actions to be performed by manager agents; refrain policies that define actions that subjects must refrain from performing; and delegation policies that define what authorisations can be delegated and to whom. Filtered actions extend authorisations and allow the transformation of input or output parameters to be defined. Constraints specify limitations on the applicability of policies while meta-policies define semantic constraints on permitted policies. Policy groups define a scope for related policies to which a common set of constraints can apply. Roles define a group of policies relating to positions within an organisation. Relationships define a group of policies pertaining to the interactions between a set of roles. Management structures define a configuration of role instances as well as the relationships between them. This document defines the grammar for the various types of policies in EBNF and provides simple examples of the constructs.
New Adaptive Algorithms for the Rapid Identification of Sparse Impulse Responses

This book intends to provide highlights of the current research in signal processing area and to offer a snapshot of the recent advances in this field. This work is mainly destined to researchers in the signal processing related areas but it is also accessible to anyone with a scientific background desiring to have an up-to-date overview of this domain. The twenty-five chapters present methodological advances and recent applications of signal processing algorithms in various domains as telecommunications, array processing, biology, cryptography, image and speech processing. The methodologies illustrated in this book, such as sparse signal recovery, are hot topics in the signal processing community at this moment. The editor would like to thank all the authors for their excellent contributions in different areas of signal processing and hopes that this book will be of valuable help to the readers.
Transposed-letter effects in reading.

TRANSPOSED-LETTER EFFECTS IN READING SEPTEMBER 2004 REBECCA LINN JOHNSON, B.A., GEORGETOWN COLLEGE M.A., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Keith Rayner Three eyetracking experiments were conducted to explore the role of letter identity and letter position during normal silent reading. Before fixating on a target word within each sentence, readers were provided with a parafoveal preview that differed in the amount of useful letter identity and letter position information it provided. Previews in all three experiments fell into one of five conditions: (1) identical to the target word (e.g., clerk as the preview of clerk), (2) involved a transposition of two internal letters (e.g., celrk), (3) involved a substitution of two internal letters (e.g., cohrk), (4) involved a transposition of the two final letters (e.g., clekr), or (5) involved a substitution of the two final letters (e.g., clefn). In Experiment 1, when targets were five letters in length, the identity condition yielded shorter viewing duration times than the other conditions, including the mean of the transposed-letter (TL) conditions and the mean of the final-manipulation conditions. The TL conditions provided greater preview benefit than the substituted-letter (SL) conditions at both letter manipulation positions. In Experiment 2, when parafoveal word shape congruency was manipulated, the pattern of data replicated Experiment 1 . The TL-internal condition, however, was more similar to the identity condition in the
Spatial Outlier Detection Approaches and Methods: A Survey

An outlier is any object which is inconsistent with the remaining objects in a database in data mining the outlier detection plays an interesting and important role because the removal of false outliers may affect the mined results to a greater extent if it is important information needed for analysis. The Spatial outliers are locations which are significantly different from their neighborhoods even though they are not much deviated from the entire population. It helps in finding out the local instabilities of objects when compared with other objects in spatial data. The spatial exploration becomes important because it is applied in many applications like weather prediction, clinical traits, geospaced information processing etc.The detection of spatial outliers is necessary for analysis in this area. This paper presents a survey and study of spatial outliers, its approaches, detection methods and algorithms with their complexity along with their pros and cons.
Discretization and approximation methods for reinforcement learning of highly reconfigurable systems

Discretization and Approximation Methods for Reinforcement Learning of Highly Reconfigurable Systems. (December 2009) Amanda Kathryn Lampton, B.S., Texas A&M University; M.S., Texas A&M University Chair of Advisory Committee: Dr. John Valasek There are a number of techniques that are used to solve reinforcement learning problems, but very few that have been developed for and tested on highly reconfigurable systems cast as reinforcement learning problems. Reconfigurable systems refers to a vehicle (air, ground, or water) or collection of vehicles that can change its geometrical features, i.e. shape or formation, to perform tasks that the vehicle could not otherwise accomplish. These systems tend to be optimized for several operating conditions, and then controllers are designed to reconfigure the system from one operating condition to another. Q-learning, an unsupervised episodic learning technique that solves the reinforcement learning problem, is an attractive control methodology for reconfigurable systems. It has been successfully applied to a myriad of control problems, and there are a number of variations that were developed to avoid or alleviate some limitations in earlier version of this approach. This dissertation describes the development of three modular enhancements to the Q-learning algorithm that solve some of the unique problems that arise when working with this class of systems, such as the complex interaction of reconfigurable parameters and computationally intensive models of the systems. A multi-resolution state-space discretization method is developed that adaptively rediscretizes the state-space by progressively finer grids around one or more distinct Regions Of Interest within the state or learning space. A genetic algorithm that autonomously selects the basis functions to be used in the approxi-
Detection of targets in presence of strong jammers by adaptive beamforming

A study is made of a matched system for detecting a target in the presence of background noise and strong jammers. The ideal receiver is analytically computed using classical decision theory, and its performances, which gives the upper bounds of the problem, is evaluated for a given scenario. Adaptive beamforming is then shown to be a good approximation of the unrealizable ideal receiver, and its performance is measured in simulation using the same scenario as for the ideal receiver. A comparison is made of the performance of the two systems. <<ETX>>
Robust Bayesian FDR Control with Bayes Factors

This paper proposes a new procedure to perform simultaneous testing of multiple hypotheses using Bayes factors as input test statistics. One of the most significant features of this method is its robustness in controlling the targeted false discovery rate (FDR) even under misspecifications of parametric alternative models. Moreover, the proposed procedure is highly computationally efficient, which is ideal for treating big data. We investigate the theoretical properties of the new procedure and demonstrate its use under various complex scenarios.
La formación académica sobre los libros y la lectura a través de los estudios de comunicación no verbal

Con el creciente uso de medios audiovisuales, los estudios de comunicacion no verbal ofrecen una gran ayuda para la formacion de ninos, adolescentes y adultos como lectores de libros impresos, sensibilizandolos a su interaccion con los libros como objetos de apreciacion sensorial e intelectual y enriqueciendo su "acto de lectura". Se trata de hacerles conscientes de la compleja red de componentes verbales y no verbales que forman un texto literario (mas las multiples funciones de sus posibles ilustraciones graficas), con experiencias sensoriales (directas y, muy importante, sinestesicas) e inteligibles, entre ellas sonidos somaticos, extrasomaticos y ambientales descritos o evocados en el texto impreso, y silencios explicitos o implicitos que tambien debemos vivir durante la lectura. A todo esto deben anadirse cuatro dimensiones estudiadas tambien aqui: la influencia en cada lector de sus circunstancias personales y del entorno durante la lectura; la deseable oralizacion muda o audible del texto por el lector; las caracteristicas del acto de lectura cuando esta seriamente limitado por diversos estados de interaccion reducida, como ceguera o paralisis; y la atraccion retroactiva en lectores adultos de los libros leidos en su infancia y adolescencia, por lo que debe fomentarse el cuidado de sus libros a esas edades.
Object-Oriented Software Development: A Practical Guide

1. Introduction. 2. The Iterative Development Process. 3. The O-O Development Methodology. 4. Software Development Phases. 5. Putting It All Together. Appendix A: References. Appendix B: Tool References. Appendix C: Methodology Summary. Appendix D: Complete ATM Application. Appendix E: Requirements Specification Outline. Appendix F: Development Team Roles. Appendix G: Build Cycle. Appendix H: Sample Line Item Schedule and Description. Appendix I: Measurements and Metrics. Appendix J: Smalltalk Coding Standards.
Part of Speech Tagging Guidelines for Penn Korean Treebank

This document describes the Part-of-Speech (POS) tagging guidelines for the Penn Korean Treebank Project. The corpus used for this project consists of around 54,000 words and 5,000 sentences. This document starts with a summary of the tagset used in the Penn Korean Treebank, followed by a more detailed discussion of each tag with examples. Then pairs of tags that are easily confused with each other are discussed and guidelines on how to distinguish one from the other for a given base forms and inflections are presented. The document concludes with a list of specific problematic examples with guidelines on how to handle such cases.
Authentication and authorization in multilevel security systems for public administration

The article contains a brief survey of the different approaches to authentication and authorization in distributed systems and the new concept of the authentication and authorization based on multilevel security features. Proposed idea should be particularly useful in public administration systems. Such systems can consist of many separated subsystems with completely different authentication mechanisms. The goal of the paper was to develop a prototype of Authentication and Authorization System (AAS in short) to supervise access to the data applications operating in the information systems of public administration
Analysis and designing of the stable parallel packet switch

The parallel packet switch attracts a lot of attention from the communications equipment vendors since it can be practically applied into terabit switches and routers. In order to accelerate its recognition and deployment, we attempt to present the detailed analysis of stability for the parallel packet switch architecture. A model of the stable parallel packet switch (SPPS) is proposed. Then the constraints of traffic dispatch algorithms, the number of layers and internal speedup for the SPPS are theoretically analyzed. Based on these results an example of designing SPPS architecture with 1.28 T capacity is presented. Simulations were carried out to investigate the validity and practicality of the designed SPPS.
BGP Query Answering against Dynamic RDF Databases

A promising method for efficiently querying RDF data consists of translating SPARQL queries into efficient RDBMS-style operations. However, answering SPARQL queries requires handling RDF reasoning, which must be implemented outside the relational engines that do not support it. We introduce the expressive database (DB) fragment of RDF for which we devise novel sound and complete techniques for answering Basic Graph Pattern (BGP) queries. Our techniques explore the two established approaches for handling RDF semantics, namely reformulation and saturation; we show how they cope with updates, a complex problem due to the rich RDF semantics. Our algorithms can be deployed on top of any RDBMS(-style) engine, and we experimentally study their performance trade-offs.
Unified Probabilistic Models for Face Recognition from a Single Example Image per Person

This paper presents a new technique of unified probabilistic models for face recognition from only one single example image per person. The unified models, trained on an obtained training set with multiple samples per person, are used to recognize facial images from another disjoint database with a single sample per person. Variations between facial images are modeled as two unified probabilistic models: within-class variations and between-class variations. Gaussian Mixture Models are used to approximate the distributions of the two variations and exploit a classifier combination method to improve the performance. Extensive experimental results on the ORL face database and the authors' database (the ICT-JDL database) including totally 1,750facial images of 350 individuals demonstrate that the proposed technique, compared with traditional eigenface method and some well-known traditional algorithms, is a significantly more effective and robust approach for face recognition.
The Effectiveness of Using Litle Shop of Treasures Game in Mastering English Vocabulary at the Fifth Grade Students at SDN Kutoanyar 02 Tulungagung

Keyword : Effectiveness, Little Shop of Treasures Game, Vocabulary Mastery Little shop of treasures game is one of the hidden object game series from game house. It can be played online or as a game house. In this case, little shop of treasures game refer to hidden object game series that is played as game house. It’s commonly use to help teach children how to increase their vocabulary. The teacher just prepares some small pictures to sell to the students and the students should to buy the pictures by the name of the pictures that are prepared before in a box, so the students not buy with money. The formulation of the research problem is how effective is little shop of treasures game in teaching vocabulary of the fifth grade students of SDN Kutoanyar 02 Tulungagung? The objective of this study is to find out how effective is using little shop of treasures game toward vocabulary mastery achievement of the fifth grade students of SDN Kutoanyar 02 Tulungagung. Research method: 1) the research design in this study was pre-experimental design with quantitative approach. 2) the subject of this study was the fifth grade students of SDN Kutoanyar 02 consisting of 27 students. 3) the research instrument was test. 5) the data analysis was using T test with help spss 16.00. The result showed that the result of the significant level is 0.00%. It is known that the significant level in the table is less than 0.05%= 0.00% < 0.05%. This means that Ha which states that there is significant effect in the vocabulary achievement after the students are taught by using little shop of treasures game is accepted. Whereas Ho which states that there is no significant effect in the vocabulary achievement after the students are taught by using little shop of treasures game is rejected. In other words, little shop of treasures game can be used as an alternative to teach vocabulary mastery to the students at elementary school level. The suggestion are: 1) the teacher and the students expected to use little shop of treasures game in teaching learning process, especially in vocabulary mastery, 2) the future researcher expected to conduct this research in similar area, especially on using little shop of treasures game, but in other school
The analysis of noun sequences using semantic information extracted from on-line dictionaries

This dissertation describes a computational system for the automatic analysis of noun sequences in unrestricted text. Noun sequences (also known as noun compounds or complex nominals) have several characteristics which prove to be obstacles to their automatic interpretation. First, the creation of noun sequences is highly productive in English; it is not possible to store all the noun sequences that will be encountered while processing text. Second, their interpretation is not recoverable from syntactic or morphological analysis. Interpreting a noun sequence, i.e., finding the relation between the nouns in a noun sequence, requires semantic information, both in limited domains and in unrestricted text. The semantic analysis in previous computational systems relied heavily on the availability of domain-specific knowledge bases; these have always been handcoded. In this dissertation, we will describe a new approach to the problem of interpreting noun sequences; we also propose a new classification schema for noun sequences, consisting of 14 basic relations/classes. The approach involves a small set of general rules for interpreting NSs which makes use of semantic information extracted from the definitions in on-line dictionaries; the process for automatically acquiring semantic information will be described in detail. Each general rule can be considered as the configuration of semantic features and attributes on the nouns which provide evidence for a particular noun sequence interpretation; the rules access a set of 28 semantic features and attributes. The rules test relatedness between the semantic information and the nouns in the noun sequence. The score for each rule is not determined by the presence or absence of semantic features and attributes, but by the degree to which the nouns are related. The results show that this system interprets 53% of the noun sequences in previously unseen text. An analysis of the results indicates that additional rules are needed and that the semantic information found provides good results, but some semantic information is still missing. For these tests, only information extracted from the definitions were used; on-line dictionaries also contain example sentences which should be exploited, as well as the definitions of words other those in the noun sequence.
Fourier Bayesian networks: A novel approach for network structure inference with application to brain connectivity studies from magnetoencephalographic recordings

This thesis proposes a novel approach for connectivity studies in Electrophysiology and Neuroimaging based on Bayesian Network (BN) analysis in the Fourier domain that is named Fourier Bayesian Networks (FBNs). FBNs use the complex information available in time series to make inferences about an unknown network structure. Using the Fourier transform, the frequency power and frequency phase information are estimated; then probabilistic models using power and phase are built and used in the network structure searching algorithm. FBNs are able to deal with massive datasets with long time series and large numbers of sources. This property is inherited by the Fourier transform from which the Fourier coefficients instead of raw time series are used during network searching. The analysis of the phase using the Fourier transform makes FBNs non-parametric, meaning that these networks do not rely on a model to make inferences. This is an important property for causality inference since several network unfoldings, as in the case of Dynamic BNs, are not needed. This makes FBNs robust to the underlying model. The proposed method is tested using multivariate autoregressive (MVAR) and non-linear (NL) systems with the variable model order d. Networks are estimated from the MVAR(d) and NL(d) systems directly and also from a magnetoencephalographic (MEG)-simulated environment where beamforming is implemented for source inference. For all experiments d=1 and d=2 are used. The optimization method for network structure searching is simulated annealing.
Efficient View-dependent Rendering of Terrains

Though considerable progress has been made with the view-dependent techniques in terrain visualization, the CPU overhead still precludes their wide application in many domains. The calculation complexity of view-dependent techniques mainly involves the calculation of node screen space error every frame, including the time-consuming screen space projection, the number of nodes whose projection error remains to be updated, and the evaluation of the valid life of the projection error. In this paper we introduce block-priority-based traversal of quadtree for reducing the traversal complexity and propose view-angle-based error metrics. Thus we successfully speed up the valid life evaluation of projection error by means of calculating the spatial relation between the viewpoint and a simplified split zone. In addition, constant frame rate has been achieved by scaling the split zone accordingly. Corresponding experimental results have shown that our methods can real-time render large scale terrain on a low-cost PC so as to satisfy the demand of most applications in this way.