Miracle-dz/UniFAR-FTUs huggingface dataset:
One-Factor-Garch Models for German Stocks - Estimation and Forecasting

This paper presents theoretical models and their empirical results for the return and variance dynamics of German stocks. A factor structure is used in order to allow for a parsimonious modeling of the first two moments of returns. Dynamic factor models with GARCH dynamics (GARCH(1,1)-M, IGARCH(1,1)-M, Nonlinear Asymmetric GARCH(1,1)-M and Glosten-Jagannathan-Runkle GARCH(1,1)-M) and three different distributions for the disturbances (Normal, Student's t and Generalized Error Distribution) are considered. Out-of-sample forecasts for the stock returns based upon these models are computed. These forecasts are compared with forecasts based on individual GARCH(1,1)-M models, static factor models, naive, random walk and exponential smoothing forecasts.
Variable Selection Techniques Implemented Procedures of the SAS Software

In Different variable selection techniques are often employed in practical data analysis as part of the statistical modelling process to reduce the number of variables to be included in a 'final' analysis of the relationship under study. For example, in regression-type applications of these techniques it is the goal to obtain a final model fitting appropriately the observed data which should (i) lead to stable estimates of the model parameters, (ii) predict accurately future values of the dependent variable based on the knowledge of all explanatory variables in the model, and (iii) allow a comprehensible interpretation of the relationship under investigation. The paper describes briefly several popular variable selection techniques in different statistical contexts and looks for their implementation in procedures of the SAS software. A complete coverage of all opportunities to use these techniques within the SAS software, in particular in the SAS/STAT, SAS/ETS, SAS/OR, and SAS/QG components, is given. Selection criteria used by the different procedures, statistical details of the involved algorithms and syntactic specifications are compared. Finally, a critical discussion of the present status of implementation of variable selection techniques in the SAS software from a statistical point of view is provided.
John von Neumann Institute for Computing Modelling of Atmospheric Chemistry Transport Processes

c © 2006 by John von Neumann Institute for Computing Permission to make digital or hard copies of portions of this work for personal or classroom use is granted provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise requires prior specific permission by the publisher mentioned above.
Unemployment duration and individual heterogeneity: a regional study

This paper investigates the impact of individual heterogeneity and regional influences on unemployment duration utilizing cross-section microeconomic data drawn from a representative random survey of individual job seekers for the English county of Kent. These individual-level data are unique in that they provide information concerning the personal characteristics of job seekers, alongside direct observations of both their reservation wages and job search behaviour. Such data are rare and, to the authors' knowledge, have never before been utilized in a regional context. Thus, the paper contributes to the empirical literature by analysing the extent to which individual heterogeneity and intra-regional variation in labour market opportunities impact upon the observed distribution of unemployment duration(s). In particular, the paper analyses the extent to which the duration of unemployment is determined by individual choice. This is an important issue for the formation and evaluation of policy. These results provide new insights into the long-term efficacy of current microeconomic supply-side initiatives such as ‘The New Deal’ and related welfare to work policies. They also advocate a more active role for macroeconomic demand-led management and provide support for a more integrated strategy for policy implementation at the urban and regional level.
Collaborative Intelligence Analysis with CACHE : Bias Reduction and Information Coverage

CACHE is a system supporting collaborative analysis tasks. We describe CACHE and a study of the effects of its use on reducing confirmation bias in analysis—the tendency to seek information that confirms rather than refutes an initial belief. We compare collaborative vs individual (Nominal) use of CACHE, as well as groups made of members with diverse (Heterogeneous) beliefs vs Homogeneous beliefs. We found reduction in confirmation bias for Heterogeneous collaborative groups using CACHE and working alone, but Homogeneous groups accentuated initial biases, rather than debiasing. Benefits of CACHE, future extensions, and our perspective on design are discussed.
A fractional-sampling-rate ADC-based CDR with feedforward architecture in 65nm CMOS

ADC-based CDRs take digital samples of the received signal to recover the clock and data. Digital representation of the signal allows for extensive channel equalization in the digital domain. Recently-reported ADC-based CDRs sample the signal at 1× or 2× the baud rate. The 1× CDR aligns the sampling clock with the signal using a phase-tracking feedback loop [1–2], which requires a voltage-controlled oscillator or phase interpolator, both analog circuits, to adjust the phase of the sampling clock. To eliminate these analog circuits (and their phase control) in favor of an all-digital implementation, a blind-sampling ADC-based CDR (top of Fig. 8.6.1) samples the received signal at 2× without phase locking to the signal. The CDR then interpolates between the blind samples to obtain a new set of samples in order to recover the phase and data [3–4]. The doubling of the sampling rate, however, increases the ADC power consumption or, equivalently, reduces the maximum baud rate due to the conversion-rate limitations of ADCs.
The difficulty of (so-called) self-embedded structures *

Why is it impossible to process The rat the cat the dog chased ate died? The standard explanations all focus on its syntactic structure, but the present paper offers an alternative explanation in terms of semantic structure. The syntactic account cannot explain why some sentences which are syntactically similar are much easier to process. The difficult sentences seem to be those in which an embedded clause which modifies a noun has its own subject modified by another clause whose subject is a common noun (not a pronoun). The explanation offered here is that the senses of the modified nouns are not sufficiently distinct to be maintained as separate concepts in short-term memory, so the various concepts stored 'interfere' with one another.
Accounting for whiteness through collaborative fiction

ABSTRACT This arts-based, qualitative teacher-researcher study considers how a group of mostly white high school students worked with their white facilitators to consider whiteness using Youth Participatory Action Research in conjunction with playbuilding and drama pedagogy. First, the author locates his reflexive stance. Then, relying on critical race theory and critical whiteness theory, the author uses narrative inquiry to share an ethnographic vignette that considers how students located, defined, and articulated their understanding of whiteness.
Intelligent and Effective Decision Support System Using Multilayer Perceptron

Medical science industry has huge amount of data, but most of this data is not mined to find out hidden information in data. Diagnosing of heart disease is one of important issue to develop medical decision support system which will help the physicians to take effective decision. In this paper an attempt is made to study the applicability supervised feed forward neural network. It uses backpropagation learning algorithm with momentum term and augmented learning rate . Missing data are handled using the substituting mean method. Performance of this technique is measured through sensitivity, specificity, accuracy and ROC. We have enhanced the performance of MLP using Dagging approach. In our study 10-fold cross validation method was used to measure the unbiased estimate of the model. Cleveland dataset was used for empirical comparisons.
Who cares and does it matter for the labour market?: A longitudinal analysis of the labour force status of indigenous and non-indigenous carers

Indigenous Australians experience higher rates of severe or profound disability than other Australians and the gap in rates of disability between Indigenous and non- Indigenous Australians increases with age. The relatively high rates of disability amongst the Indigenous population lead to relatively heavy caring burdens. Relatively little is known about the impact of caring on the employment rates of Indigenous carers and virtually nothing about the impact of caring on changes in labour force status. This paper uses the recently released Australian Census Longitudinal Dataset to analyse the labour market dynamics of Indigenous and non-Indigenous carers and the extent to which these differ from the dynamics of those who are not carers. We also examine how labour force status changes, in association with commencement as a carer and exiting from caring. The analysis raises questions about how caring decisions are made within households and the extent to which the costs of caring may differ between Indigenous and non-Indigenous households.
The detection of French accent by American listeners.

The five experiments presented here examine the ability of listeners to detect a foreign accent. Computer editing techniques were used to isolate progressively shorter excerpts of the English spoken by native speakers of American English and French. Native English-speaking listeners judged the speech samples in one- and two-interval forced-choiced tests. They were able to detect foreign accent equally well when presented with speech edited from phrases read in isolation and produced in a spontaneous story. The listeners accurately identified the French talkers (63%-95% of the time) no matter how short were the speech samples presented: entire phrases (e.g., "two little dogs"), syllables (/tu/ or /ti/), portions of syllables corresponding to the phonetic segments /t/,/i/,/u/, and even just the first 30 ms of "two" (roughly, the release burst of /t/). Both phonetically trained listeners familiar with French-accented English and unsophisticated listeners were able to accurately detect accent. These results suggest that listeners develop very detailed phonetic category prototypes against which to evaluate speech sounds occurring in their native language.
Quality dependent multimodal fusion of face and iris biometrics

Although iris is known as the most accurate and face as the most accepted in biometrics, these distinct modalities encounter variability in data in real-world applications. Such limitation can be overcome by a multimodal system based on both traits. Additionally, by conditioning the multimodal fusion on quality, useful information can be extracted from lower quality measures rather than rejecting them out of hand. This paper suggests a dynamic weighted sum fusion that exploits an iris occlusion-based quality metric while combining unimodal scores. Instead of incorporating the quality of the gallery and probe images separately, a single quality metric for each gallery-probe comparison was used. Two strategies for integrating this metric into score-level fusion were explored. Experiments on the IV2 multimodal database including multiple variabilities proved that the proposed method improves some best current non quality-based fusion schemes by more than 30% in terms of Equal Error Rates.
High speed CABAC codecs for DSP- and FPGA-based platforms

In this paper, two original structures of Context-based Adaptive Binary Arithmetic Codec (CABAC) are proposed for real-time video compression systems. Two proposed CABAC codecs were implemented and optimized for DSP-based platform and FPGA-based platform respectively. Analysis of implementations of proposed CABAC codecs was done. Both the software and hardware version of CABAC codec was tested in terms of entropy codec throughput. Number of clock cycles needed to process a binary symbol was measured for software version of CABAC as well as hardware version of CABAC.
His Bundle Electrogram in Bundle‐Branch Block

Because a great majority of patients with chronic complete heart block have bilateral bundle-branch lesions, it becomes important to recognize earlier degrees of bilateral bundle-branch block. The H-V interval in the His bundle electrogram during unilateral bundle-branch block reflects the conduction primarily through the contralateral bundle branch, and thus the His bundle electrogram in bundle-branch block (BBB) provides information regarding the functional status of the contralateral bundle branch in addition to helping in the localization of defects elsewhere in the conduction system.His bundle electrograms were obtained in 20 patients with BBB and 13 patients without BBB. The following results were obtained from this study: (1) Prolonged P-R interval in the absence of BBB indicated delayed conduction through the A-V node. (2) Prolonged P-R interval in the presence of BBB indicated delayed conduction through the contralateral bundle branch or through the A-V node, or both. (3) Delayed conduction through the contralateral bundle branch in BBB occurred in the presence of a normal P-R interval and could only be detected by demonstrating a prolonged H-V time in the His recording. (4) In alternating BBB the His recording clearly demonstrated that the changing P-R interval was related to varying conduction through the bundle branches. (5) Finally, it has been demonstrated that the Wenckebach (Mobitz type I) type of decremental conduction can occur in the bundle branches or Purkinje system as well as in the A-V node.It is concluded that His bundle electrograms provide valuable information concerning the nature and management of conduction disturbances in patients with bundle-branch disease.
Modelling the galaxy bimodality: shutdown above a critical halo mass

We reproduce the blue and red sequences in the observed joint distribution of colour and magnitude for galaxies at low and high redshifts using hybrid N-body/semi-analytic simulations of galaxy formation. The match of model and data is achieved by mimicking the effects of cold flows versus shock heating coupled to feedback from active galactic nuclei (AGNs), as predicted by Dekel and Birnboim. After a critical epoch z ∼ 3, only haloes below a critical shock-heating mass M shock ∼ 10 12 Menjoy gas supply by cold flows and form stars, while cooling and star formation are shut down abruptly above this mass. The shock-heated gas is kept hot because being dilute it is vulnerable to feedback from energetic sources such as AGNs in their self-regulated mode. The shutdown explains in detail the bright-end truncation of the blue sequence at ∼L ∗, the appearance of luminous red-and-dead galaxies on the red sequence starting already at z ∼ 2, the colour bimodality, its strong dependence on environment density and its correlations with morphology and other galaxy properties. Before z ∼ 2-3, even haloes above the shock-heating mass form stars by cold streams penetrating through the hot gas. This explains the bright star forming galaxies at z ∼ 3-4, the early appearance of massive galaxies on the red sequence, the high cosmological star formation rate at high redshifts and the subsequent low rate at low redshifts.
A framework for evaluating network measures for functional importance

Many metrics such as degree, closeness, and PageRank have been introduced to determine the relative importance of a node within a network. The desired function of a network, however, is domain-specific. For example, the robustness can be crucial for a communication network, while efficiency is more preferred for fast spreading of advertisements in viral marketing. The information provided by some widely used measures are often conflicting under such varying demands. In this paper, we present a novel framework for evaluating network metrics regarding typical functional requirements. We also propose an analysis of five well established measures to compare their performance of ranking nodes on functional importance in a real-life network.
Improving ERP Requirement Specification Process of SMEs with a Customer-Centered Analysis Method

Nowadays enterprise resource planning (ERP) systems are mostly ready-made software packages, which raises the importance of the ERP system selection. For SMEs a good fit between company business processes and ERP system functionality is a top priority in ERP selection. However, SME companies’ resources are limited and quite often their experience and knowledge of ERP systems is inadequate. Current models of software requirement specification are too expensive and cumbersome for SMEs. Typically, these models are targeted at supporting the implementation process after the software selection. In this study we first present the characteristics of SMEs’ ERP projects and through case studies discuss how they could be evolved more effectively. We then propose a new advanced method for SMEs’ ERP requirement specification that includes operational, contextual and risk analysis. Together these analyses provide a complete in-depth description of company business process development, specify the requirements for the new ERP system, and identify the restrictions and risks related to the ERP project. The results of a case study in which the method has been applied, support further development towards a holistic and multidisciplinary approach in the ERP requirements specification process of SMEs.
High-speed communication network for controls with the application on the exoskeleton

Our lower extremity exoskeleton is a wearable robotic device that enables a human to walk with a load for a prolonged period of time without reducing the human's agility. The exoskeleton comprised of two anthropomorphic legs and a spine. The device is designed and controlled autonomously via a spine mounted internal combustion engine and PC104 compliant computer. Custom hardware was designed to accommodate the high-speed network required to link the distributed sensors and actuators. This paper presents the implementation of the high-speed hard real-time network designed to maintain stable control of the exoskeleton during stance and walk. The high-speed ring protocol necessary to maintain strict hard real-time synchronization between the distributed sensors and actuator of the exoskeleton is presented. Communication latency was considered in the design with respect to its impact on performance, and stability. Error detection and recovery was crucial for operation with the exoskeleton. A cyclic redundancy check (CRC) algorithm was incorporated into the protocol to achieve this error detection. The use of this high-speed serial based network greatly minimized the number of cables required over traditional parallel-based systems. The achieved update time of up to 10 kHz for a six-actuator system enables the architecture to be viable system for most industrial controls.
Dynamically Evolving, Large-scale

One frequently studied problem in the context of information dissemination in communication networks is the broadcasting problem. In this paper, we study the following randomized broadcasting protocol: At some time t an information r is placed at one of the nodes of a graph G . In the succeeding steps, each informed node chooses one neighbor, independently and uniformly at random, and informs this neighbor by sending a copy of r to it. First, we consider the relationship between randomized broadcasting and random walks on graphs. In particular, we prove that the runtime of the algorithm described above is upper bounded by the corresponding mixing time, up to a logarithmic factor. One key ingredient of our proofs is the analysis of a continuous-type version of the afore mentioned al-gorithm, which might be of independent interest. Then, we introduce a general class of Cayley graphs, including (among others) Star graphs, Transposition graphs, and Pancake graphs. We show that randomized broadcasting has optimal runtime on all graphs belonging to this class. Finally, we develop a new proof technique by combining martingale tail estimates with combinatorial methods. Using this approach, we show the optimality of our algorithm on another Cayley graph and obtain new knowledge about the runtime distribution on several Cayley graphs.
An abstraction for awareness management in collaborative virtual environments

This paper describes an object-oriented abstraction for the problem of awareness management in Collaborative Virtual Environments (CVEs). The described abstraction allows for different types of awareness information and awareness management policies to be used. It is also described how the defined abstraction was used to support the awareness management policies of two demo CVEs application.
Estimate the Primary-Link SNR Using Full-Duplex Relay for Underlay Spectrum Sharing

In cognitive radio networks, the signal-to-noise ratio (SNR) of the primary receiver (PR), called primary-link SNR, is critical for underlay spectrum sharing. However, it is very difficult for the cognitive user (CU) to obtain the primary-link SNR. In this letter, we propose a new method to let the CU autonomously estimate the primary-link SNR, where the full-duplex relay technique is used. Then, the CU can conduct the underlay spectrum sharing more efficiently. Simulation results indicate the effectiveness of the proposed method.
Expression of glutamine synthetase and glutamate dehydrogenase by marine bacterioplankton: Assay optimizations and efficacy for assessing nitrogen to carbon metabolic balance in situ

Expression of glutamate metabolism enzymes, glutamate dehydrogenase (GDH), and glutamine synthetase (GS) are proposed to yield information on the nitrogen (N) to carbon (C) metabolic balance within bacterioplankton communities. Whole‐cell assay conditions were optimized, and reactions were linear with time and biomass. Enzyme activities were assayed in seawater cultures from four ecosystems of contrasting trophic state amended with different regimes of glucose, amino acids, and ammonium (NH4+) to validate expression patterns of GDH and GS in various combinations of N and C limitation or excess. In three of four experiments, glucose amendment enhanced GS expression by 2‐fold but repressed GDH by 10% to 40% relative to the control. In contrast, addition of amino acids or NH4+ resulted in 20% to 90% repression of GS and enhanced GDH expression by 20% to 900%. The GDH:GS activity ratio (×10−3) ranged from 6 to 22 in glucose added treatments and 63 to 264 in NH4+‐amended treatments and appears to be a more sensitive index of bacterial N bioavailability relative to C supply than either enzyme alone. Cluster analysis was used to identify the condition of ambient bacterio‐plankton by matching enzyme expression with the validation results. This enzymatic approach overcomes some of the biases and limitations of other methods for assessing N metabolism in marine bacteria while providing unique information to further understand constraints of bacterioplankton respiration, production, and N flux.
A context-aware orchestrating and choreographic test framework for service-oriented applications

Service orientation is an approach to developing software applications by means of service orchestration and choreography. In such applications, a service interacts with not only other services but also its embedding environment via contexts. However, it is still unclear about how to develop effective testing techniques for service orchestration and choreography, particularly in the presence of contexts. In this article, we present a context-aware framework for testing service-oriented applications.