Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear timing acquisition scheme in DS-CDMA communication system

Timing estimation has been shown an important issue in multiuser communication (Buehrer et al. 1996). Chang and Chen (1997) proposed the optimum timing estimation and confirmed the need of two-stage timing recovery policy: acquisition and tracking. While the complexity of the tracking scheme applying the gradient search algorithm increases linearly to the number of users, the timing acquisition still has non-polynomial (NP) complexity. Timing acquisition with linear complexity, as an M-ary hypothesis testing problem, is therefore needed in practical multiuser communications. This paper not only points out the difference between the design of a linear timing acquisition scheme and the linear detector, but also proposes a novel, simple, and effective criterion for linear timing acquisition design. With a discrete timing assumption, we prove that the estimation error of the linear timing acquisition scheme based on this new criterion converges to zero in L/sup 2/ as the SNR increases to infinity for an arbitrary number of users. In the general case of continuous timing, explanations and simulation results are provided to demonstrate the effectiveness of the linear acquisition scheme by the new criterion. We demonstrate such a linear scheme existing in interference limited operation for an arbitrary number of users.
Re-Engagement into Care : The Role of Social Support on Service Use for Recurrent Episodes of Mental Health Distress Among Primary Care Patients

Given high rates of relapse of depression, understanding mechanisms that provide long-term benefits and optimal outcomes for depressed individuals is crucial. The current study examines social support as a relevant component in service use to manage mental health needs for individuals with recurrent depression over a 5-year period. Conducting a secondary data analysis from a randomized clinical trial titled Partners in Care, the study examines direct and moderating effects over two time points of reported 12-month social support on service use for mental health needs at 57-months for an adult sample (n = 991). Direct effects were supported for demographic and need variables. Increased social support at 12-months positively moderated the relationship between health impairment and service use at 57-months. Findings inform and extend the understanding of social support as an important mechanism to care to integrate into the treatment experience, encouraging service use to manage recurrent depressive episodes.
Boundary Element Analysis Of The Multi-capsuleFlow Using An Ultra-high Speed GPGPUComputation

A capsule is a liquid drop enclosed by a thin membrane. Understanding the mechanics of capsule suspension is important in a variety of applications. However, computational time is still a barrier against successful simulations for dense suspension of capsules. We have developed an ultra-high speed computation method based on Graphics Processing Unit (GPU) computing for simulating multicapsule flow. In the case of using single GPU, the performance achieves 1.20 TFlops that corresponds to a 550-fold speed up compared with a CPU core. We also developed an algorithm of multi GPUs that hide data communication by overlapping with computational time. Since our method enables us to simulate from one to a few hundred capsules in a realistic computational time, the method could be a powerful solution for simulating the capsule suspension.
Arithmetic coding architecture for H.264/AVC CABAC compression system

In this paper we propose an efficient implementation of CABAC's binary arithmetic coder and context management system. CABAC is the context adaptive binary arithmetic coder used in new H.264/AVC video standard. Arithmetic coding allows a significant enhancement in compression. However, implementation complexity is a drawback due to hardware cost and slowness. In this paper we show the need for a hardware implementation of arithmetic coding in current video compression systems. We propose a fast and efficient implementation of the encoding algorithm. We prove that memory accesses constitute a bottleneck and propose solutions that apply to the encoding algorithm and context management system. As a result, a fast architecture is presented, able to process one symbol per cycle.
Mandatory IFRS adoption and analyst forecast accuracy: the role of financial statement-based forecasts and analyst characteristics

This study examines whether the improvement in analyst forecast accuracy around mandatory IFRS adoption is associated with the improvement in the accuracy of financial statement-based forecasts. We find significant out-of-sample improvement in financial statement-based forecast accuracy around mandatory IFRS adoption and significant improvement in analyst forecast accuracy only in countries that made concurrent improvements to financial reporting enforcement. We show that the improvement in analyst forecast accuracy is associated with the improvement in financial statement-based forecast accuracy around IFRS adoption. We also show that analyst forecasts, particularly for firms whose analysts forecast under favorable conditions (i.e., analysts who are less busy with more experience and resources), have a greater association with financial statement-based forecasts, after mandatory IFRS adoption in countries with concurrent changes in enforcement.
FCI‐based Multiple Choice Test for Investigating Students' Representational Coherence

We present the Representation Test derived from the FCI for evaluating students' representational coherence on some aspects of gravitation and Newton's third law. The test consists of 23 questions addressing verbal, graphical, bar chart, and vectorial representations. Matched high school student data (n = 54) on the pre‐ and post‐test are analyzed in terms of representational coherence and scientific correctness.
Design and Evaluation of Cloud Network Optimization Algorithms

This dissertation tries to give a deep understanding of the impact of the new Cloud paradigms regarding to the Traffic Engineering goal, to the Energy Efficiency goal, to the fairness in the endpoints offered throughput, and of the new opportunities given by virtualized network functions.In the first part of our dissertation we investigate the impact of these novel features in Data Center Network optimization, providing a formal comprehensive mathematical formulation on virtual machine placement and a metaheuristic for its resolution. We show in particular how virtual bridging and multipath forwarding impact common DCN optimization goals, Traffic Engineering and Energy Efficiency, assess their utility in the various cases in four different DCN topologies.In the second part of the dissertation our interest move into better understand the impact of novel attened and modular DCN architectures on congestion control protocols, and vice-versa. In fact, one of the major concerns in congestion control being the fairness in the offered throughput, the impact of the additional path diversity, brought by the novel DCN architectures and protocols, on the throughput of individual endpoints and aggregation points is unclear.Finally, in the third part we did a preliminary work on the new Network Function Virtualization paradigm. In this part we provide a linear programming formulation of the problem based on virtual network function chain routing problem in a carrier network. The goal of our formulation is to find the best route in a carrier network where customer demands have to pass through a number of NFV node, taking into consideration the unique constraints set by NFV.
Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists

Preface Introduction 1. Graphical representation of biochemical systems 2. Models of biochemical systems 3. From maps to equations 4. Computer simulation 5. Parameter estimation 6. Analytical steady-state evaluation 7. Sensitivity analysis 8. Case study 1 - Anaerobic fermentation pathway in Saccharomyces cerevisiae 9. Case study 2 - diagnosis and refinement of a model of the tricarboxylic acid cycle in Dictyostelium discoideum 10. Case study 3 - A sequence of models describing purine metabolism 11. Case study 4 - Algebraic analysis of the initial steps of the Glycolytic-Glycogenolytic pathway in perfused rat liver 12. Epilogue-Canonical modeling beyond biochemistry Appendix Hints and solutions References Author index Subject index.
Asset volatility

We examine whether fundamental measures of volatility are incremental to market-based measures of volatility in (i) predicting bankruptcies (out of sample), (ii) explaining cross-sectional variation in credit spreads, and (iii) explaining future credit excess returns. Our fundamental measures of volatility include (i) historical volatility in profitability, margins, turnover, operating income growth, and sales growth; (ii) dispersion in analyst forecasts of future earnings; and (iii) quantile regression forecasts of the interquartile range of the distribution of profitability. We find robust evidence that these fundamental measures of volatility improve out-of-sample forecasts of bankruptcy and help explain cross-sectional variation in credit spreads. This suggests that an analysis of credit risk can be enhanced with a detailed analysis of fundamental information. As a test case of the benefit of volatility forecasting, we document an improved ability to forecast future credit excess returns, particularly when using fundamental measures of volatility.
Theoretical and Experimental Modal Analysis

An elongated fishing lure formed, in the preferred embodiment, entirely of a soft, elastic, flexible and resilient plastic material which results in a lure freely deformable or manipulable under external forces. The lure includes an elongated body, a head at one end and a tail at the second end, with a series of integral outwardly projecting ribs at closely spaced points along the body, which ribs perform multiple significant functions including the selective trapping and release of air, the generation of clear acoustical signals, the increase in the visual bulk of the lure without affecting the flexibility thereof, the provision of means for facilitating movement of the lure over obstacles, etc.
Are Writing Deficiencies Creating a Lost Generation of Business Writers?

Business professionals and instructors often view writing skills as one of the most important qualifications that employees should possess. However, many business employees, including recent college graduates, have serious writing deficiencies, especially in their ability to use standard English. As a result, American businesses spend billions of dollars annually to remediate these writing deficiencies (College Board, the National Commission on Writing for America's Families, Schools, and Colleges, 2004). In this article, the authors examine possible reasons for these deficiencies and offer evidence that a modified context-based approach, the glossing approach, and consistent error marking can reduce the number of sentence-level errors students make.
An Approach to Building Rough Data Model Through Supervised Fuzzy Clustering

A new method for fast building the rough data model (RDM) by means of supervised fuzzy clustering in the product space of input and output variables is proposed. The approach incorporates the RDM’s classification quality performance index with Gustafson-Kessel (GK) clustering algorithm and is of many good properties. The way to convert the fuzzy cluster models to rough data models by introducing the concept of putative membership degree of a data point to a fuzzy cluster is suggested. Hence, an efficient algorithm that can obtain RDMs by just iteratively computing two necessary condition equations is worked out. It minimizes the objective function and turns the multi-dimensional search process of the Kowalczyk’s method to one dimensional search strategy (in terms of the number of clusters). This technique reduces the searching time greatly. Compared with the traditional rough set theory and the Kowalczyk’s method, the approach has more powerful ability to handle data contaminated by noise and better generalization ability. Finally, different examples of data sets illustrate the effectiveness of the approach.
Link analysis and impact of top universities of Islamic world on the world wide web

Purpose – This purpose of this paper is to report on an analysis of linkages and impact of top universities of Islamic Countries on the web.Design/methodology/approach – The AltaVista search engine was used to calculate universities' number of links and web impact factors.Findings – The results revealed that half of the universities have not scored well in the indexes used by the webometrics ranking model. Among all universities, King Saud University of Saudi Arabia scored well in most indexes.Originality/value – The paper presents a look at the functions and performance of top universities' web sites of Islamic countries.
MULTIPLE REPRESENTATIONS AND FREE-BODY DIAGRAMS: DO STUDENTS BENEFIT FROM USING THEM?

ABSTRACT OF THE DISSERTATION Multiple Representations and Free-Body Diagrams: Do Students Benefit from Using Them? By David Rosengrant Dissertation Director: Prof. Eugenia Etkina Introductory physics students have difficulties understanding concepts and solving problems. When they solve problems, they use surface features of the problems to find an equation to calculate a numerical answer often not understanding the physics in the problem. How do we help students approach problem solving in an expert manner? A possible answer is to help them learn to represent knowledge in multiple ways and then use these different representations for conceptual understanding and problem solving. This solution follows from research in cognitive science and in physics education. However, there are no studies in physics that investigate whether students who learn to use multiple representations are in fact better problem solvers. This study focuses on one specific representation used in physics – a free body diagram. A free-body diagram is a graphical representation of forces exerted on an object of interest by other objects. I used the free-body diagram to investigate five main questions: iii
Network Systems Design Using Network Processors

From the Publisher: Acknowledged computer networking expert Douglas Comer has authored the first-ever textbook on networking processors. Dr. Comer offers both professionals and advanced students comprehensive instruction on how to design and build network systems using the latest network processor technology. This unique text explains the software and hardware architectures used to implement the Internet, including switches, routers, bridges, NAT boxes, firewalls, intrusion-detection systems and load balancers.
Corelex: systematic polysemy and underspecification

CoreLex: Systematic Polysemy and Underspeci cation A dissertation presented to the Faculty of the Graduate School of Arts and Sciences of Brandeis University, Waltham, Massachusetts by Paul Buitelaar This thesis is concerned with a uni ed approach to the systematic polysemy and underspeci cation of nouns. Systematic polysemy { senses that are systematically related and therefore predictable over classes of lexical items { is fundamentally di erent from homonymy { senses that are unrelated, non-systematic and therefore not predictable. At the same time, studies in discourse analysis show that lexical items are often left underspeci ed for a number of related senses. Clearly, there is a correspondence between these phenomena, the investigation of which is the topic of this thesis. Acknowledging the systematic nature of polysemy and its relation to underspeci ed representations, allows one to structure ontologies for lexical semantic processing more e ciently, generating more appropriate interpretations within context. In order to achieve this, one needs a thorough analysis of systematic polysemy and underspeci cation on a large and useful scale. The thesis establishes an ontology and semantic database (CoreLex) of 126 semantic types, covering around 40,000 nouns and de ning a large number of systematic polysemous classes that are derived by a careful analysis of sense distributions inWordNet. The semantic types are underspeci ed representations based on generative lexicon theory. The representations are used in underspeci ed semantic tagging, addressing two problems in traditional semantic tagging: sense enumeration (the di culty on deciding the number of discrete senses), due to systematic polysemy; and multiple reference (NP's denoting more than one model-theoretic referent), due to underspeci cation. Also, traditional semantic tags that are based on discrete senses tend to be too ne-grained for practical use. For instance, WordNet has, in principle, around vi 60,000 di erent tags (synsets) for nouns alone. The CoreLex approach, on the other hand, o ers a concise set of 126 tags that are inherently more coarse-grained, by taking into account systematic polysemy and underspeci cation. Underspeci ed semantic tagging is implemented, using probabilistic classi cation in order to cover unknown nouns (not in CoreLex) and to identify context-speci c and new interpretations. The classi cation algorithm is centered around the computation of a Jaccard (similarity) score that compares lexical items in terms of the attributes (linguistic patterns acquired from domain speci c corpora) they share. vii
Computer self-efficacy and classroom practice : what is the correlation?

The present technological focus in education is requiring teachers to become computer-literate so that they are better able to integrate computer technology into their teaching. This thesis examines teachers' levels of computer self-efficacy (one's belief in one's ability to use computers) to see if there is a correlation with computer self-efficacy and classroom practice. Current research suggests that one can use computer self-efficacy as a way of determining teachers' levels of willingness to use computers. Based on the distribution of a computer self-efficacy scale and a questionnaire designed to identify computer technology integration into teaching, this study shows the correlation between computer self-efficacy and classroom practice in a selection of schools in southern Alberta. The findings of the research show that there is a weak correlation (r = 0.405) between CSE and classroom practice; while there is a moderate to strong correlation (r = 0.62) between CSE and instructional practice. Interestingly, the correlations between CSE and each of the specific classroom uses listed in the survey were extremely weak. These correlation coefficients ranged from 0.077-0.287. Only 14/87 of the teachers surveyed have not attended a computer course. However, out of those 14 teachers only 2 do not use the computer for classroom use. On the other hand, of the 73 teachers who have attended a computer course, 16 do not use the computer in classroom teaching. For this group of teachers, participating in a computer course did not appear to have an impact on classroom practice. Moreover, the research found that those teachers with high levels of CSE do not necessarily teach using computers. An exploration of change literature provides a framework for understanding these
Depth of Vocabulary Knowledge

Depth of vocabulary knowledge refers to how well words are known. Developing vocabulary depth typically involves the accumulation of knowledge through encountering and using words in a variety of different contexts in order to learn the forms, meanings, and uses of words. Keywords: assessment methods in applied linguistics; esl/efl; language teaching; vocabulary
Outline of a Mathematical Theory of Computation

However, Scott does realize that the approach argued for above is simply an argument for an approach that accomodates human understanding of computation and that the operational approach must not be ignored because, as he points out, the machines that the programs of study run on are not capable of dealing with such an abstract level of understanding. That is, the computaional approach should not be abandoned because the machines that we build operate on that lower level.
The size Ramsey number of graphs with bounded treewidth

A graph $G$ is Ramsey for a graph $H$ if every 2-colouring of the edges of $G$ contains a monochromatic copy of $H$. We consider the following question: if $H$ has bounded treewidth, is there a `sparse' graph $G$ that is Ramsey for $H$? Two notions of sparsity are considered. Firstly, we show that if the maximum degree and treewidth of $H$ are bounded, then there is a graph $G$ with $O(|V(H)|)$ edges that is Ramsey for $H$. This was previously only known for the smaller class of graphs $H$ with bounded bandwidth. On the other hand, we prove that the treewidth of a graph $G$ that is Ramsey for $H$ cannot be bounded in terms of the treewidth of $H$ alone. In fact, the latter statement is true even if the treewidth is replaced by the degeneracy and $H$ is a tree.
Statistical Inference and Feasibility Determination: A Nonasymptotic Approach

We develop non-asymptotically justified methods for hypothesis testing about the p-dimensional coefficients in (possibly nonlinear) regression models, where the hypotheses can also be nonlinear in the coefficients. Our (nonasymptotic) control on the Type I and Type II errors holds for fixed n and does not rely on well-behaved estimation error or prediction error; in particular, when the number of restrictions in the null hypothesis is large relative to p-n, we show it is possible to bypass the sparsity assumption on the coefficients (for both Type I and Type II error control), regularization on the estimates of the coefficients, and other inherent challenges in an inverse problem. We also demonstrate an interesting link between our framework and Farkas' lemma (in math programming) under uncertainty, which points to some potential applications of our method outside traditional hypothesis testing.
Posterior Contraction Rates for Gaussian Cox Processes with Non-identically Distributed Data

This paper considers the posterior contraction of non-parametric Bayesian inference on non-homogeneous Poisson processes. We consider the quality of inference on a rate function $\lambda$, given non-identically distributed realisations, whose rates are transformations of $\lambda$. Such data arises frequently in practice due, for instance, to the challenges of making observations with limited resources or the effects of weather on detectability of events. We derive contraction rates for the posterior estimates arising from the Sigmoidal Gaussian Cox Process and Quadratic Gaussian Cox Process models. These are popular models where $\lambda$ is modelled as a logistic and quadratic transformation of a Gaussian Process respectively. Our work extends beyond existing analyses in several regards. Firstly, we consider non-identically distributed data, previously unstudied in the Poisson process setting. Secondly, we consider the Quadratic Gaussian Cox Process model, of which there was previously little theoretical understanding. Thirdly, we provide rates on the shrinkage of both the width of balls around the true $\lambda$ in which the posterior mass is concentrated and on the shrinkage of posterior mass outside these balls - usually only the former is explicitly given. Finally, our results hold for certain finite numbers of observations, rather than only asymptotically, and we relate particular choices of hyperparameter/prior to these results.