Miracle-dz/UniFAR-FTUs huggingface dataset:
A/D converter performance analysis by a frequency domain approach

An analysis of the frequency domain approach in the test of analog-to-digital convertors (ADCs) is presented. Following the introduction of a spectral analysis algorithm based on the use of windows with minimum sidelobe energy, expressions are given to determine ADC performance parameters. Corrections are introduced to improve accuracy in practical cases, and simulation results are presented to support the discussion. The approach presented is sufficiently precise in the characterization of a device, even with data records of comparatively small size. Provided the appropriate correction factors are taken into account in some determinations, the accuracy is not dissimilar to that of other test methods, with the advantage that both data acquisition and data processing procedures are fairly simple. <<ETX>>
Designing a Literature Instruction Using Big Data

Digital paradigms became a reality and now all pay attention on how the world around us is changing and react accordingly. In particular, the increasing importance of computational thinking continues to reframe the dialogue appropriate and effective instruction. Literature instructors are also today being forced to think about 'how to teach', rather than 'what to teach'. Aware of the issues, this paper proposes a new instructional model using big data suitable to be used to teach literary history and provides learners, who had grown up surrounded with an excess of technology and media use in everyday life, opportunities to make literary studies more attractive and easier to understand. Through this, it attempts to explore theoretically educational methodology of studying literary history in order to encourage learners' meaningful participation in classroom.
Tema 2: The NAO robot as a Persuasive Educational and Entertainment Robot (PEER) – a case study on children’s articulation, categorization and interaction with a social robot for learning

The application of social robots as motivational tools and companions in education is increasingly being explored from a theoretical and practical point of view. In this paper, we examine the social robot NAO as a Persuasive Educational and Entertainment Robot (PEER) and present findings from a case study on the use of NAO to support learning environments in Danish primary schools. In the case study we focus on the children’s practice of articulation and embodied interaction with NAO and investigate the role of NAO as a ‘tool’, ‘social actor’ or ‘simulating medium’ in the learning designs. We examine whether this categorization is static or dynamic, i. e. develops and changes over the course of the interaction and explore how this relates to and affects the student’s motivation to engage in the NAO-supported learning activities.
A Survey of Identity-based Signcryption

Abstract Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously, at a cost significantly lower than that required by the traditional signature-then-encryption approach. Signcryption has found many applications, such as electronic transaction protocol, mobile agent protocol, key management, and routing protocol. In this article, the state-of-the-art of identity-based signcryption (IBSC) is surveyed. We examine the security model of IBSC. We survey the existing IBSC schemes and compare their security properties and efficiency. IBSC with special properties and identity-based hybrid signcryption are investigated. Some possible future work is also pointed out.
The PMU-Based Power System Dynamic State Estimation Using Extended Kalman Filter

Abstract. Dynamic state estimation of power system is a sophisticated problem since voltage and current phasors under dynamic conditions are nonlinear and hard to be obtained. This paper presents a new power system dynamic state estimation method using Extended Kalman Filter (EKF) based on Phasor Measurement Unit (PMU). EKF can be used to deal with nonlinear system. With the help of PMU which is the key unit of Wide Area Measurement Systems (WAMS), continuous time waveforms with high accuracy and synchronized time stamps can be estimated. In case study, the effectiveness of the proposed method has been evaluated by dynamic state estimation of 3-bus powers system in Matlab, and scenarios with different PMU placement are compared. The proposed method achieves high accuracy in all these scenarios.
OntOAIr: a method to construct lightweight ontologies from document collections

Ontologies are key components in the development of the Semantic Web, as they provide a shared understanding of a domain. However, acquiring the knowledge to construct ontolo- gies is a costly task that requires much time and many resources. This work describes OntOAIr, a semi-automatic construction method of lightweight ontologies from document collections. The OntOAIr method uses simplified representations of documents, an adaptation of the Frequent Itemset-based Hierarchical Clus- tering algorithm (FIHC), and ontological engineering techniques. We present experimental results and we describe applications that use the constructed ontologies
Experiments of on-line path following under joint limits for an industrial robot manipulator

This paper presents an experimental case study concerning the application of an on-line inverse kinematics algorithm ensuring tracking of the assigned end-effector path to a six-dof industrial robot manipulator. The desired trajectory to be followed by the manipulator in the presence of velocity and acceleration joint limits is generated on-line while the robot manipulator is in motion. Path tracking is achieved by properly slowing down the task-space trajectory via a time warp when joint limits are encountered. The experimental results confirm the effectiveness of the adopted algorithm and show that the desired path is kept as much as possible.
Highly efficient digital CMOS accelerator for image and graphics processing

This paper presents a novel high-bandwidth digital accelerator for image and graphics processing applications. The proposed architecture outperforms previously proposed processing-in-memory architectures in speed, area and power by up to several orders of magnitude. Several variations of the design have been implemented in 2.5 V 0.25 /spl mu/m and 1.8 V 0.18 /spl mu/m CMOS technology.
Testes de Segurança em Redes sem Fio com o Uso do Software Reaver

Tecnologias sem fio abrangem diversas capacidades orientadas para diferentes usos e necessidades. Dispositivos de Rede Local sem Fio (WLAN – Wireless Local Area Network), permitem que os usuários movam seus computadores portáteis de um local para o outro, sem a necessidade de fios e sem perder a conectividade de rede. Menos fiação significa uma maior flexibilidade, maior eficiência e redução de custos [1]. Redes locais sem fio são geralmente utilizadas como extensões para as infra-estruturas cabeadas existentes e fornecem a interface entre clientes sem fio e estações rádio-base ou pontos de acesso. Adicionalmente, clientes sem fio podem se comunicar de um modo independente. Organizações e indústrias estão constantemente trabalhando para melhorar a taxa de dados, alcance e segurança em soluções de rede sem fio [2]. Por outro lado, a mobilidade das WLANs também proporciona problemas de segurança que devem ser considerados. As atuais soluções de segurança em redes sem fio foram desenvolvidas em duas etapas. A primeira, chamada de WiFi Protected Access (WPA), anunciada pela Wi-Fi Alliance no final de 2002, projetada especificamente para permitir a atualização da maioria dos softwares em sistemas sob gerência da Wi-Fi Alliance. A segunda, uma nova versão da norma IEEE 802.11, Wi-Fi Protected Access, Version 2 (WPA2) ou IEEE 802.11i, foi apresentada em 2004 com o objetivo de oferecer maiores nı́veis de segurança comparados ao padrão anterior [3]. Nesse contexto, o Wi-Fi Protected Setup (WPS) é um protocolo de certificação opcional da Wi-Fi Alliance, projetado para facilitar a tarefa de instalar e configurar a segurança em redes locais sem fio. Uma maneira de explorar falhas presentes em roteadores sem fio, com o WPS habilitado, é por meio do software Reaver. O Reaver é um sistema de ataque para redes com protocolos WPA, que explora uma falha de projeto no protocolo WPS. Esta vulnerabilidade expõe um ataque de
Two-stage carrier synchronization techniques for nonselective fading

Transmitted reference carrier synchronization techniques can potentially provide near-coherent performance in the presence of time-varying fading. Such techniques are spectrally not as efficient as nonreference-based architectures and can have performance several dB worse than ideal coherent in higher order modulations (e.g., 64-QAM). This paper presents a two-stage demodulator that facilitates improved spectral efficiency or provides better performance (or sometimes both). The two-stage architecture results from examining the optimal detector for M-QAM. The first stage produces tentative decisions and removes the modulation from the received signal. The second stage implements a smoothing filter for the resulting signal, providing an improved carrier estimate. Monte Carlo simulation results demonstrate the improved performance For 4-QAM, 16-QAM, and 64-QAM. >
How Does Arithmetic Demystify Growth Success: the Taiwanese Case

This paper studies the productivity improvement in economies experiencing rapid structural transformation. In particular, it identifies the productivity growth that attribute to reallocating labor from a low to a high productivity sector in Taiwan from 1951 to 2003. For the Taiwanese case, the macroeconomic statistics show that the percentage of population working in the agricultural sector fell sharply. Meanwhile, the overall economy grew rapidly. Therefore, a question arises about whether such rapid growth and structural transformation are connected. To address this question, I begin by comparing productivity growth across East Asian, Latin American and OECD countries. The results show that those which grew fast also experienced rapid labor reallocation from a farm to a non-farm sector. Using Taiwan as a detailed case study, I show applying simple arithmetic to look into productivity under a two-sector rather than a one-sector framework reduces the measured productivity growth by 28% in terms of total factor productivity. In other words, the result shows factors, especially labor, reallocating from a low productive sector to a high productive one plays an un-deniable role in accounting for the high productivity improvement in an economy experiencing rapid structural transformation.
Bayesian nonparametric and semi-parametric methods for incomplete longitudinal data

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy BAYESIAN NONPARAMETRIC AND SEMI-PARAMETRIC METHODS FOR INCOMPLETE LONGITUDINAL DATA By Chenguang Wang August 2010 Chair: Michael J. Daniels Major: Statistics We consider inference in randomized longitudinal studies with missing data that is generated by skipped clinic visits and loss to follow-up. In this setting, it is well known that full data estimands are not identified unless unverified assumptions are imposed. Sensitivity analysis that assesses the sensitivity of model-based inferences to such assumptions is often necessary. In Chapters 2 and 3, we posit an exponential tilt model that links non-identifiable distributions and identifiable distributions. This exponential tilt model is indexed by non-identified parameters, which are assumed to have an informative prior distribution, elicited from subject-matter experts. Under this model, full data estimands are shown to be expressed as functionals of the distribution of the observed data. We propose two different saturated models for the observed data distribution, as well as shrinkage priors to avoid the curse of dimensionality. The two procedures provide researchers different strategies for reducing the dimension of parameter space. We assume a non-future dependence model for the drop-out mechanism and partial ignorability for the intermittent missingness. In a simulation study, we compare our approach to a fully parametric and a fully saturated model for the distribution of the observed data. Our methodology is motivated by, and applied to, data from the Breast Cancer Prevention Trial.
ADS Mode-S channel performance for aircraft surveillance using GPS positioning

Mode S squitter technology is being considered as the basis of an automatic dependent surveillance (ADS) system. Under this proposal, aircraft positions would be determined by GPS equipped aircraft and the Mode S data link would be used to transmit the positional information, along with current Mode S usage. This paper studies the downlink data channel of the Mode S data link. The downlink channel is modeled as a random access ALOHA channel in both a fading and non-fading signal environments. The paper presents results for both unslotted (pure ALOHA) and slotted channel performance for Mode S GPS data traffic.
A bound on signal-to-quantizing noise ratios for digital encoding systems

When an analog signal is encoded into digital form and then decoded back into an analog signal, quantizing noise is always introduced. The amount of quantizing noise which contaminates the decoded analog signal is inextricably tied to the amount of redundancy present in the signal and in the digital bit stream. Reducing the quantizing noise and, therefore, increasing the fidelity of the resulting signal requires that the redundancy in the digital bit stream be reduced or eliminated. There is a point, however, beyond which the quantizing noise cannot be further reduced. This is discussed in quantitative terms by deriving an upper bound on the signal-to-quantizing noise power ratio possible for a given bit rate and signal ensemble. Ratios of signal-to-quantizing noise greater than this bound are not possible for digital encoding systems. This bound is compared with the operation of pulse code modulation, differential pulse code modulation, and delta modulation systems.
DISCOVERING SIMILAR ORGANIZATIONAL SOCIAL MEDIA STRATEGIES USING CLASSIFICATION AND CLUSTERING

Organisations have been striving to account for the resources they’ve been allocating to Social Media integration and management, essentially because this integration has been occurring without a previously designed content strategy, which will foster the desired fan engagement. In order to establish a comparison of social media strategies between HEIs, we developed a seven category model, encompassing the fundamental communication areas of focus for higher education service providers. Then, we performed a classification of these HEI posts in Facebook, according to our model. For this step, we used six of the most promising, and prominent, classifiers to obtain a predicted category for each post. Combining all posts from each HEI according to the model we get the HEI’s editorial strategy. By clustering the overall social media strategies and corresponding response rate we discover the sector’s monitoring HEI and, through a benchmarking process, we retrieve useful inputs for the design of social media strategies for HEI.
A comparative analysis of paging and location update strategies for PCS networks

Several alternative strategies for reducing paging and location update costs have been proposed in the literature. This paper compares four well-known strategies, that differ in the manner they approach the problem. The same mobility model and evaluation criteria was used for all strategies analyzed. Users are classified according to the call-to-mobility-ratio (CMR). Results are given weighting in different ways: the signaling cost in the radio interface and in the fixed network part.
RECURSION IS NOT LANGUAGE DOMAIN-SPECIFIC: INTERIM RESULTS OF A RESEARCH PROGRAM

In this manuscript we will present the interim results of our research program, focused on answering the question of whether recursion is language domain-specific. We will review behavioral, developmental and imaging studies. Overall, our results suggest that recursion can be used in non-linguistic domains, and that this usage does not require verbal resources. However interesting parallels exist across domains.
Bayesian Neural System identification: error bars, receptive fields and neural couplings

The task of system identification lies at the heart of neural data analysis. Bayesian system identification methods provide a powerful toolbox which allows one to make inferences over stimulus-neuron and neuron-neuron dependencies in a principled way. Rather than reporting only the most likely parameters, the posterior distribution obtained in the Bayesian approach informs us about the range of parameter values that are consistent with the observed data and the assumptions made. In other words, Bayesian receptive fields always come with error bars. Since the amount of data from neural recordings is limited, the error bars are as important as the receptive field itself.
An entropy metric for software maintainability

An entropy metric that can be calculated from readily available data for existing software is presented. Commercially available software provides data on the message flow in software, which are used to calculate changes in the entropy loading during software maintenance. Since entropy increases indicate increases in the disorder of the software system, entropy loading can be used as a metric in software maintenance. <<ETX>>
A Trace Macroscopic Description based on Time Aggregation

Today, because of computing system complexity, it is required to trace application executions to understand their behavior. Visualization techniques provide some help in representing their content, but their scalability is limited both because of human perception and bounded screen resolution. To solve this issue, we propose a visualization based on time aggregation that provides a concise overview of a trace whatever its size. The level of details in this visualization can be configurable by users who can adjust the compromise between concision (gain from aggregation) and information loss. They can then refine their analysis by zooming in an interesting part and choosing a less aggregated overview for this interesting part. This visualization is implemented in our tool, Ocelotl, which enables users to interact with this visualization by changing the selected time interval and its aggregation settings dynamically. The results presented in this paper show that the technique can help users correctly identify anomalies in very large trace files composed of up to forty million events.
Comparison of Head-related Transfer Function Models Based on Principal Components Analysis

이 연구는 중앙면 상에서 주성분 분석법을 이용하여 시간 및 주파수 영역에서 머리전달함수의 모형화 기법들을 다룬다. 시간영역의 머리전달함수, 복소수 값의 머리전달함수, 확장된 머리전달함수, 로그 크기의 머리전달함수에 기반하여 각각 주성분 분석법을 수행하여 얻은 네 가지 머리전달함수 모형들에 대해서 최소자승오차 관점에서 모형화 성능을 비교하고, 모형들간의 이론적인 관계를 살펴보는 것이 이 연구의 목적이다. 모형화에 사용되는 기저함수의 수가 동일하다면, 시간영역에서의 머리전달함수 혹은 확장된 머리전달함수에 기반한 모형이 복소수 값의 머리전달함수에 기반한 모형보다 최소자승오차 관점에서 더 효율적인 모형화 성능을 지닌다. 시간영역에서의 머리전달함수에 기반한 모형과 확장된 머리전달함수에 기반한 모형은 이론적으로 동일한 모형이며 서로 푸리에 변환 관계가 있다. 로그 크기의 머리전달함수에 기반한 모형은 다른 모형들과 모형화 성능 및 이론적인 관계를 비교할 수가 없는데, 이는 로그 크기의 머리전달함수에 기반한 모형은 머리전달함수의 크기 정보만을 로그 크기로 다루는 반면에 다른 모형들은 선형 크기로 머리전달함수의 크기와 위상정보를 모두 다루기 때문이다.
Bionics solution to learn the arm reaching with collision avoidance

This article presents a learning model that simulates the control of an anthropomorphic arm kinematics motion. The objective is to reach and grasp a static prototypic object placed behind different kinds of obstacle in size and position. The network, composed of two generic neural network modules, learns to combine multi-modal arm-related information trajectory parameters as well as obstacle-related information obstacle size and location. Our simulation was based on the notion of Via Point, which postulates that the motion planning that is divided into specific successive position of the arm. In order to determine these special points, an experimental protocol has been built and pertinent parameters have been integrated to the model. According to these studies, we propose an original method that takes into account the previous learning modules to determine the entire trajectory of the wrist in order to reach the same object placed behind two successive obstacles. The aim of this approach is to understand better the impact of experience in a task realisation and show that learning can be performed from previous initiation. Some results applied to obstacle avoidance task show the efficiency of the proposed method.
Scaleable audio service for collaborative virtual environments over Internet

We describe an audio-service for network applications, designed to support many simultaneous speakers and to operate across the Internet. Our service exploits a technique called distributed partial mixing to dynamically adapt to varying numbers of speakers and network congestion. A collection of networked audio mixers is arranged as a distributed graph. Each mixes subsets of its input audio streams into one or more mixed streams, which it forwards along with any unmixed streams. This reduces network traffic but at the cost of also reducing the audio quality. An experiment demonstrates how our implementation dynamically manages the trade-off between congestion and audio quality when compared to the approaches of peer-to-peer forwarding and total mixing. We also demonstrate how our approach can be realised in a way that is fair to the TCP protocol and so operates as a "good Internet citizen".
Visualization on Supercomputing Platform Level II ASC Milestone (3537-1B) Results from Sandia

This report provides documentation for the completion of the Sandia portion of the ASC Level II Visualization on the platform milestone. This ASC Level II milestone is a joint milestone between Sandia National Laboratories and Los Alamos National Laboratories. This milestone contains functionality required for performing visualization directly on a supercomputing platform, which is necessary for peta-scale visualization. Sandia's contribution concerns in-situ visualization, running a visualization in tandem with a solver. Visualization and analysis of petascale data is limited by several factors which must be addressed as ACES delivers the Cielo platform. Two primary difficulties are: (1) Performance of interactive rendering, which is most computationally intensive portion of the visualization process. For terascale platforms, commodity clusters with graphics processors(GPUs) have been used for interactive rendering. For petascale platforms, visualization and rendering may be able to run efficiently on the supercomputer platform itself. (2) I/O bandwidth, which limits how much information can be written to disk. If we simply analyze the sparse information that is saved to disk we miss the opportunity to analyze the rich information produced every timestep by the simulation. For the first issue, we are pursuing in-situ analysis, in which simulations are coupled directly with analysis librariesmore » at runtime. This milestone will evaluate the visualization and rendering performance of current and next generation supercomputers in contrast to GPU-based visualization clusters, and evaluate the performance of common analysis libraries coupled with the simulation that analyze and write data to disk during a running simulation. This milestone will explore, evaluate and advance the maturity level of these technologies and their applicability to problems of interest to the ASC program. Scientific simulation on parallel supercomputers is traditionally performed in four sequential steps: meshing, partitioning, solver, and visualization. Not all of these components are necessarily run on the supercomputer. In particular, the meshing and visualization typically happen on smaller but more interactive computing resources. However, the previous decade has seen a growth in both the need and ability to perform scalable parallel analysis, and this gives motivation for coupling the solver and visualization. « less