Miracle-dz/UniFAR-FTUs huggingface dataset:
SpherWave : An R Package for Analyzing Scattered Spherical Data by Spherical Wavelets

Shortly before the end of 2007 it’s a great pleasure for me to welcome you to the third and Christmas issue of R News. Also, it is the last issue for me as editorial board member and before John Fox takes over as editor-in-chief, I would like to thank Doug Bates, Paul Murrell, John Fox and Vince Carey whom I had the pleasure to work with during the last three years. It is amazing to see how many new packages have been submitted to CRAN since October when Kurt Hornik previously provided us with the latest CRAN news. Kurt’s new list starts at page 57. Most of us have already installed the first patch release in the 2.6. 0 series. The most important facts about R 2.6. 1 are given on page 56. The contributed papers in the present issue may be divided into two groups. The first group focuses on applications and the second group reports on tools that may help to interact with R. Sanford Weisberg and Hadley Wickham give us some hints when our brain fails to remember the name of some important R function. Patrick Mair and Reinhold Hatzinger started a CRAN Psychometrics Task View and give us a snapshot of current developments. Robin Hankin deals with very large numbers in R using his Brobdingnag package. Two papers focus on graphical user interfaces. From a high-level point of view, John Fox shows how the functionality of his R Commander can be extended by plug-in packages. John Verzani gives an introduction to low-level GUI programming using the gWidgets package. Applications presented here include a study on the performance of financial advices given in the Mad Money television show on CNBC, as investigated by Bill Alpert. Hee-Seok Oh and Donghoh Kim present a package for the analysis of scattered spherical data, such as certain environmental conditions measured over some area. Sebastián Luque follows aquatic animals into the depth of the sea and analyzes their diving behavior. Three packages concentrate on bringing modern statistical methodology to our computers: Parametric and semi-parametric Bayesian inference is implemented in the DPpackage by Alejandro Jara, Guido Schwarzer reports on the meta package for meta-analysis and, finally, a new version of the well-known multtest package is described by Sandra L. Taylor and her colleagues. The editorial board wants to thank all authors and referees who worked with us in 2007 and wishes all of you a Merry Christmas and a Happy New Year 2008!
Applying the fuzzy analytic network process to the selection of an advanced integrated circuit (IC) packaging process development project

In the modern business environment, process technology evaluation and selection (PTES) is a crucial component of innovation in new product development (NPD). The most difficult task for project managers in PTES is to make the optimal technology choice for a Research and Development (R&D) project, and there are many attendant uncertainties and risks in process technology R&D projects for NPD. Recently, Integrated Circuit (IC) Packaging has become an equal part of the cost-performance equation in the silicon world, and packaging foundries have responded quicker than many other semiconductor companies to the rapidly changing requirements of chip-scale packaging. This facilitates the transfer of new technology from the assemblers to the chip suppliers. This study applies the fuzzy analytic network process (FANP) model to evaluate the strategic impact of new IC manufacturing technologies in firms within Taiwan’s IC packaging industry. Our study will determine the key decision-making factors affecting R&D project selection using FANP, and additionally we develop an optimal manufacturing process. As a case study, the ongoing “Controller IC packaging R&D project A” was chosen to minimize warpage of controller IC.
HEMATOPOIESIS AND STEM CELLS Nonredundant and locus-speci fi c gene repression functions of PRC 1 paralog family members in human hematopoietic stem / progenitor cells

Department of Experimental Hematology and Department of Laboratory Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Department of Experimental and Clinical Medicine, University of Catanzaro Magna Græcia, Catanzaro, Italy; Biogem Scarl, Institute for Genetic Research Geatano Salvatore, Ariano Irpino, Italy; Laboratory of Molecular Hematopoiesis, University of Catanzaro Magna Græcia, Catanzaro, Italy; and Department of Biochemistry, Groningen Biomolecular Sciences and Biotechnology Institute, Netherlands Proteomics Centre & Zernike Institute for Advanced Materials, University of Groningen, Groningen, The Netherlands
Why Most Open Source Development Projects Do Not Succeed?

Evidence suggests that only a small percentage of open source development (OSSD) projects are active, have significant participation, or have delivered operational software. We develop a system dynamics based simulation model to analyze the dynamics of open source project participation process and software development process. We show that the complex interaction between participation and development processes affects crucially success or failure.
Uptake dynamics of scrapie agent in the intestinal villous epithelium of suckling and weanling Syrian hamsters

In mice, the number of intestinal villous columnar epithelium cells that incorporate abnormal prion protein (PrPSc) decreases significantly after weaning. In this study, the dynamics of PrPSc uptake during the growth of hamsters were investigated by inoculating scrapie 263K agent orally into suckling and weanling Syrian hamsters and estimating the number of PrPSc‐positive villous epithelium cells immunohistochemically. The number of PrPSc‐positive cells declined significantly as the hamsters aged. The present results suggest that a tendency toward decline of PrPSc‐positive cells with increasing age might be a common phenomenon among the superfamily Muridae.
An Amplify-and-Forward Scheme for Spectrum Sharing in Cognitive Radio Channels

In this paper, we propose a cognitive radio scheme that allows a secondary user (SU) to transmit over the same time-frequency slot of a primary user (PU), even when the PU is active. In our scheme, the SU amplifies and forwards the signal of the PU, by using as scaling factor the value of its information symbol to be transmitted towards the secondary receiver. The information-theoretic limits of the proposed protocol are investigated in terms of ergodic channel capacities of both the PU and SU links. It is shown that: 1) under certain operating conditions, the SU can superimpose its information symbols on the PU signal, without violating the cognitive radio principle of protecting the PU transmission; and 2) when the primary link is busy, the SU offers the PU its own transmitting power in exchange for a low-capacity communication channel, which improves the packet delay performance of the SU. In this barter, the tempting incentive for the PU consists of a noticeable improvement of its achievable rate at the price of a slight increase in the computational complexity of the primary receiver.
Responsive Visualization for Musical Performance

We present a framework that facilitates the visualization of live musical performance using virtual and augmented reality technologies. In order to create a framework suitable for developing technologically augmented artistic applications, we have defined our system in a way that is modular and incorporates intuitive development processes when possible. In this paper we present a method of musical feature extraction and provide three examples of music visualization applications that we have developed using our system. Our visualizations illustrate features in live singing and keyboard playing using responsive virtual characters, responsive video imagery, and responsive virtual spaces.
Package structure and manufacturing method thereof

Disclosed is a package structure which includes a loading substrate, a first connection substrate, a first chip, a dielectric glue slice, a second chip and a second connection substrate. The loading substrate is provided with first electrical contact pads and second electrical contact pads. The first connection substrate is provided with third electrical contact pads and forth electrical contact pads. Each forth electrical contact pad is in mutual electrical breakover with a corresponding first electrical contact pad. The first chip is provided with first electrode pads. Each first electrode pad is in mutual electrical breakover with a corresponding third electrical contact pad. The second chip is in mutual connection with the first chip through the dielectric glue slice. The second chip is provided with second electrode pads. The second connection substrate is provided with fifth electrical contact pads and sixth electrical contact pads which are in one-to-one correspondence with the second electrical contact pads. Each fifth electrical contact pad is in one-to-one corresponding breakover with the second electrode pads. Each sixth electrical contact pad is in mutual electrical breakover with a corresponding second electrical contact pad. The invention also provides a manufacturing method of the package structure.
Detecting electrical activity from Martian dust storms

We present a model addressing the possible electrification of Martian dust storms based on the effective electrical charging of an individual dust grain. An upper charge bound on a grain can be determined based on the grain capacitance in the low-pressure Martian atmosphere. It is assumed that treiboelectric and inductive processes, like that presumed operating in terrestrial dust storms, can electrify the grain to significant levels. A collection of such grains charged in a dust cloud of many tens of kilometers in size can yield a substantial electric field moment. Given various grain charge and dust storm sizes, the electric moment will be determined along with estimates of electrical discharge and emitted radio power based upon known models. We also suggest the possibility that remote detection of discharge-related VLF emission propagating in the surface/ionosphere waveguide can be used to determine subsurface conductivity.
Collaboration of Web Search Result through AutomaticAnnotation

Web search engines retrieved the large amount of data that is stored in the web database. Internet is the best way to access the data across the world and it present information in user friendly manner. Search engines are designed to retrieved information matching with the user query. When query is submitted web pages are retrieved.Web pages may contain several results set (SRRs). SRR is the collection of data units that represent the real world entity. Now-a-days there is a high demand for extracting and assigning a meaningful label to data units. Many applications like ecommerce and digital libraries required such a system. Therefore an automatic annotation system is used that extracted out data units and aligned them into groups and ensured that each data unit under a group has same semantic with the other data units of the same group. This automatic annotation approach is highly effective and resolves the problem of scalability.
A dialogue game framework with personalized training using reinforcement learning for computer-assisted language learning

We propose a framework for computer-assisted language learning as a pedagogical dialogue game. The goal is to offer personalized learning sentences on-line for each individual learner considering the learner's learning status, in order to strike a balance between more practice on poorly-pronounced units and complete practice on the whole set of pronunciation units. This objective is achieved using a Markov decision process (MDP) trained with reinforcement learning using simulated learners generated from real learner data. Preliminary experimental results on a subset of the example dialogue script show the effectiveness of the framework.
9 Controlling Cell Migration with Micropatterns

Taro Toyota1,2,3, Yuichi Wakamoto2,3, Kumiko Hayashi4 and Kiyoshi Ohnuma5 1Department of Basic Science, Graduate School of Arts and Sciences The University of Tokyo 2Research Center for Complex Systems Biology, The University of Tokyo 3Precursory Research of Embryonic Science and Technology (PRESTO) Japan Science and Technology Agency (JST) 4Department of Applied Physics, Graduate School of Engineering Tohoku University 5Top Runner Incubation Center for Academia-Industry Fusion Nagaoka University of Technology Japan
Sensor fusion under unknown associations by particle filters with clever proposal

A new method for sensor fusion under unknown associations among multiple sensors is proposed. Fundamental problem within the sensor fusion situation is huge number of the associations that prohibits enumerating all the combinations within tractable computational time. Proposed method formulates this situation in a state space model, which is highly nonlinear to deal with the unknown associations, and utilizes particle filters to estimate state of the model. Then we obtain state of the target system as well as the associations through the state estimation. We also propose clever proposal in the framework of particle filters that draws efficient particles in a sense of sub-optimality to minimize the variance of particles' weight. The proposed method is formulated in generic way, so, in principle, it can be applied to various situations for sensor fusion under unknown associations. We show an illustrative example to track sound target in a scene with sensors of two microphones and one camera.
Symbolic transfer function-based approaches to certified compilation

We present a framework for the certification of compilation and of compiled programs. Our approach uses a symbolic transfer functions-based representation of programs, so as to check that source and compiled programs present similar behaviors. This checking can be done either for a concrete semantic interpretation (Translation Validation) or for an abstract semantic interpretation (Invariant Translation) of the symbolic transfer functions. We propose to design a checking procedure at the concrete level in order to validate both the transformation and the translation of abstract invariants. The use of symbolic transfer functions makes possible a better treatment of compiler optimizations and is adapted to the checking of precise invariants at the assembly level. The approach proved successful in the implementation point of view, since it rendered the translation of very precise invariants on very large assembly programs feasible.
Simpl_eClass: Simplified potential-free evolving fuzzy rule-based classifiers

This paper presents the sequel of evolving fuzzy rule-based classifier eClass, called here as simplified evolving classifier, simpl_eClass. Similarly to eClass, simpl_eClass comprises of two different classifiers, namely zero and first order (simpl_eClass0 and simpl_eClass1). The two classifiers differ from each other in terms of the consequent part of the fuzzy rules, and the classification strategy used. The design of simpl_eClass is based on the density increment principle introduced recently in so called simpl_eTS+ approach. The rule learning in simpl_eClass does not involve computation of potential values that allows it to attain computationally much less expensive model update phase compared to eClass. As compared to other FRB classifiers, it retains all the advantages of eClass, such as being on-line and evolving, having zero and first order. In comparison with other non-fuzzy classifiers it has the advantage of interpretability and transparency (especially zero order type). The goals of this paper are to demonstrate the applicability of simpl_eTS+ to classification task, and to empirically show that the simplification of eClass to simpl_eClass by using potential-free approach does not compromise the accuracy of the classifiers. In order to attain the goals, the classifiers are tested by performing several experiments using benchmark data sets. The simpl_eClass1 classifier is also applied to the real-life problem of on-line scene categorization for low-resource devices benefiting from its low computational cost. The results obtained from the experiments endorse that simpl_eClass achieves the accuracy of eClass while simplifying rule learning process.
Separating-Plane Perspective Shadow Mapping

This paper proposes a real-time solution that is a hybrid between standard shadow mapping and any of the current methods based on perspective shadow mapping. Existing methods are known to have aliasing problems. At little extra cost, we combine two methods to minimize aliasing errors. This is done by computing a plane equation that separates the two resulting shadow maps to get the best possible area-based sampling density. An additional property of this separation plane is that objects entirely on one side of the plane only need to be rendered into one map.
Exploiting the WWW as a corpus to resolve PP attachment ambiguities

Finding the correct attachment site for prepositional phrases (PPs) is one of the hardest problems when parsing natural languages. An English sentence consisting of a subject, a verb, and a nominal object followed by a prepositional phrase is a priori ambiguous. The PP in sentence 1 is a noun attribute and needs to be attached to the noun, but the PP in 2 is an adverbial and thus part of the verb phrase.
Scaling exact multi-objective combinatorial optimization by parallelization

Multi-Objective Combinatorial Optimization (MOCO) is fundamental to the development and optimization of software systems. We propose five novel parallel algorithms for solving MOCO problems exactly and efficiently. Our algorithms rely on off-the-shelf solvers to search for exact Pareto-optimal solutions, and they parallelize the search via collaborative communication, divide-and-conquer, or both. We demonstrate the feasibility and performance of our algorithms by experiments on three case studies of software-system designs. A key finding is that one algorithm, which we call FS-GIA, achieves substantial (even super-linear) speedups that scale well up to 64 cores. Furthermore, we analyze the performance bottlenecks and opportunities of our parallel algorithms, which facilitates further research on exact, parallel MOCO.
Efficiency and Stability in Large Matching Markets

We study efficient and stable mechanisms in matching markets when the number of agents is large and individuals’ preferences and priorities are drawn randomly. When agents’ preferences are uncorrelated, then both efficiency and stability can be achieved in an asymptotic sense via standard mechanisms such as deferred acceptance and top trading cycles. When agents’ preferences are correlated over objects, however, these mechanisms are either inefficient or unstable, even in an asymptotic sense. We propose a variant of deferred acceptance that is asymptotically efficient, asymptotically stable, and asymptotically incentive compatible. This new mechanism performs well in a counterfactual calibration based on New York City school choice data.
Flexibility in task switching by monolinguals and bilinguals*

Many bilinguals routinely switch between their languages, yet mixed evidence exists about the transfer of language switching skills to broader domains that require attentional control such as task switching. Monolingual and bilingual young adults performed a nonverbal task-switching paradigm in which they viewed colored pictures of animals and indicated either the animal or its color in response to a cue. Monolinguals and bilinguals performed similarly when switching between tasks (local switch cost) in a mixed-task block, but bilinguals demonstrated a smaller mixing effect (global switch cost) than monolinguals, indicating better ability to reconfigure stimulus–response associations. These results suggest that regular practice using multiple languages confers a broader executive function advantage shown as improved flexibility in task switching.
Journal of Neuroengineering and Rehabilitation Open Access a Working Model of Stroke Recovery from Rehabilitation Robotics Practitioners

We reviewed some of our initial insights about the process of upper-limb behavioral recovery following stroke. Evidence to date indicates that intensity, task specificity, active engagement, and focusing training on motor coordination are key factors enabling efficacious recovery. On modeling, experience with over 400 stroke patients has suggested a working model of recovery similar to implicit motor learning. Ultimately, we plan to apply these insights in the development of customized training paradigms to enhance recovery.
Bootstrapping body sensor networks using human controlled LED-camera channels

Body sensor networks enable many interesting applications. In these applications, sensor networks always collect sensitive information, thus security is significant. Since most security mechanisms are based on identities and keys, we propose a human controlled LED-camera channel based hash key before knowledge identity and key distribution protocol. The protocol has two advantages. Firstly, the protocol uses human controlled LED-camera channels, thus human burden is reduced. Secondly, protocol performance is optimized for sensor nodes.
Performance analysis of time diversity combining with frequency offset for cellular IoT

In the growing context of Machine Type Communications (MTC), synthesized by the concept of Internet of Things (IoT), the need of an increased coverage pushes the industrial companies to develop efficient transmission techniques. Especially, the 3rd Generation Partnership Project (3GPP) already standardized evolutions of the 2G and 4G networks to include IoT features. These new standards share the common trait of using blind repetitions to improve the legacy coverage of the system, renewing interest for diversity combining. The present paper focuses on the IQ combiner approach which works on complex baseband samples without any previous phase synchronization. Our study evaluates the impact of the frequency offset, resulting of an imperfect frequency synchronization, on the average Signal to Noise Ratio (SNR) of IQ-combined frames. We derive new closed-forms: a first one for the statistical distribution of the residual phase angle between two consecutive symbols after imperfect frequency demodulation, a second one for the average SNR of the combined frame. These derivations allow us to highlight and quantify the negative impact of an inaccurate frequency synchronization in the context of IQ combining strategies.
Space-Efficient Re-Pair Compression

Re-Pair [5] is an effective grammar-based compression scheme achieving strong compression rates in practice. Let n, σ, and d be the text length, alphabet size, and dictionary size of the final grammar, respectively. In their original paper, the authors show how to compute the Re-Pair grammar in expected linear time and 5n + 4σ2 + 4d + √n words of working space on top of the text. In this work, we propose two algorithms improving on the space of their original solution. Our model assumes a memory word of [log2n] bits and a re-writable input text composed by n such words. Our first algorithm runs in expected O(n/ε) time and uses (1 + ε)n + √n words of space on top of the text for any parameter 0
Experimental procedures for entanglement verification

We give an overview of different types of entanglement that can be generated in experiments, as well as of various protocols that can be used to verify or quantify entanglement. We propose several criteria that, we argue, should be applied to experimental entanglement verification procedures. Explicit examples demonstrate that not following these criteria will tend to result in overestimating the amount of entanglement generated in an experiment or in inferring entanglement when there is none. We distinguish protocols meant to refute or eliminate hidden-variable models from those meant to verify entanglement.