Miracle-dz/UniFAR-FTUs huggingface dataset:
Biasing and high-order statistics from the SSRS2

We analyze different volume-limited samples extracted from the Southern Sky Redshift Survey (SSRS2), using counts-in-cells to compute the Count Probability Distribution Function (CPDF). From the CPDF we derive volume-averaged correlation functions to fourth order and the normalized skewness and kurtosis $S_3 = \bar{\xi_3}/\bar{\xi_2}^2$ and $S_4=\bar{\xi_4}/\bar{\xi_2}^3$. We find that the data satisfies the hierarchical relations in the range $0.3 \lsim \bar{\xi_2} \lsim 10$. In this range, we find $S_3$ to be scale-independent with a value of $\sim 1.8$, in good agreement with the values measured from other optical redshift surveys probing different volumes, but significantly smaller than that inferred from the APM angular catalog. In addition, the measured values of $S_3$ do not show a significant dependence on the luminosity of the galaxies considered. This result is supported by several tests of systematic errors that could affect our measures and estimates of the cosmic variance determined from mock catalogs extracted from N-body simulations. This result is in marked contrast to what would be expected from the strong dependence of the two-point correlation function on luminosity in the framework of a linear biasing model. We discuss the implications of our results and compare them to some recent models of the galaxy distribution which address the problem of bias.
Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula.
Neutrinos from the Sun: Experimental results confronted with solar models.

For standard neutrinos, recent solar neutrino results together with the assumption of a nuclear powered Sun imply severe constraints on the individual components of the total neutrino flux: ${\mathrm{\ensuremath{\Phi}}}_{\mathrm{Be}}$\ensuremath{\le}0.7\ifmmode\times\else\texttimes\fi{}${10}^{9}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$ ${\mathrm{s}}^{\mathrm{\ensuremath{-}}1}$, ${\mathrm{\ensuremath{\Phi}}}_{\mathrm{CNO}}$\ensuremath{\le}0.6\ifmmode\times\else\texttimes\fi{}${10}^{9}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$${\mathrm{s}}^{\mathrm{\ensuremath{-}}1}$, and 64\ifmmode\times\else\texttimes\fi{}${10}^{9}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$ ${\mathrm{s}}^{\mathrm{\ensuremath{-}}1}$\ensuremath{\le}${\mathrm{\ensuremath{\Phi}}}_{\mathit{p}\mathit{p}+\mathrm{p}\mathrm{e}\mathrm{p}}$\ensuremath{\le}65\ifmmode\times\else\texttimes\fi{}${10}^{9}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$ ${\mathrm{s}}^{\mathrm{\ensuremath{-}}1}$ (at 1\ensuremath{\sigma} level). The bound on ${\mathrm{\ensuremath{\Phi}}}_{\mathrm{Be}}$ is in strong disagreement with the standard solar model (SSM) prediction ${\mathrm{\ensuremath{\Phi}}}_{\mathrm{Be}}^{\mathrm{SSM}}$\ensuremath{\approxeq}5\ifmmode\times\else\texttimes\fi{}${10}^{9}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$ ${\mathrm{s}}^{\mathrm{\ensuremath{-}}1}$. We study a large variety of nonstandard solar models with low inner temperature, finding that the temperature profiles T(m) follow the homology relationship T(m)=${\mathit{kT}}^{\mathrm{SSM}}$(m), so that they are specified just by the central temperature ${\mathit{T}}_{\mathit{c}}$. There is no value of ${\mathit{T}}_{\mathit{C}}$ which can account for all the available experimental results. Even if we only consider the gallium and Kamiokande results, they remain incompatible. Lowering the cross section p${+}^{7}$Be\ensuremath{\rightarrow}\ensuremath{\gamma}${+}^{8}$B is not a remedy. The shift of the nuclear fusion chain towards the pp-I termination could be induced by a hypothetical low energy resonance in the $^{3}\mathrm{He}$${+}^{3}$He reaction. This mechanism gives a somehow better, but still bad, fit to the combined experimental data. We also discuss what can be learned from new generation experiments, planned for the detection of monochromatic solar neutrinos, about the properties of neutrinos and of the Sun.
Exact Decoding on Latent Variable Conditional Models is NP-Hard

Latent variable conditional models, including the latent conditional random fields as a special case, are popular models for many natural language processing and vision processing tasks. The computational complexity of the exact decoding/inference in latent conditional random fields is unclear. In this paper, we try to clarify the computational complexity of the exact decoding. We analyze the complexity and demonstrate that it is an NP-hard problem even on a sequential labeling setting. Furthermore, we propose the latent-dynamic inference (LDI-Naive) method and its bounded version (LDI-Bounded), which are able to perform exact-inference or almost-exact-inference by using top-$n$ search and dynamic programming.
Musical mode and visual-spatial cross-modal associations in infants and adults

The classification of major and minor musical stimuli along five dichotomous scales (happy–sad, pleasant–unpleasant, up–down, light–dark, and warm–cold colors) was investigated in two studies involving 51 children aged 4–6 years, and 168 adults. Musical stimuli were six chords and six harmonized melodies differing in mode (major, minor). Furthermore, fluid intelligence was assessed in both infants and adults. The associations between major mode and happiness and between minor mode and sadness increased from a proportion of 58% at the age of 4, to 61% at the age of 5, 72% at the age of 6, and 92% in adults. The major–up, minor–down associations were 62% in both the 5- and 6-year-olds, and increased to 84% in adults, while the major–light, minor–dark associations increased from 59% at the age of 5 to 72% in 6-year-olds and 92% in adults. Warm–cold colors were systematically associated with, respectively, major and minor stimuli in adults but not in children. Fluid intelligence was strongly related to the child’s ability to associate happy and sad faces to major and minor musical stimuli.
Trading group theory for randomness

In a previous paper [BS] we proved, using the elements of the theory of <italic>nilpotent groups</italic>, that some of the <italic>fundamental computational problems in matriz groups</italic> belong to <italic>NP</italic>. These problems were also shown to belong to <italic>coNP</italic>, assuming an <italic>unproven hypothesis</italic> concerning <italic>finite simple groups</italic>. The aim of this paper is to replace most of the (proven and unproven) group theory of [BS] by elementary combinatorial arguments. The result we prove is that relative to a <italic>random oracle B</italic>, the mentioned matrix group problems belong to (<italic>NP∩coNP</italic>)<supscrpt><italic>B</italic></supscrpt>. The problems we consider are <italic>membership</italic> in and <italic>order</italic> of a matrix group given by a list of generators. These problems can be viewed as multidimensional versions of a close relative of the discrete logarithm problem. Hence <italic>NP∩coNP</italic> might be the lowest natural complexity class they may fit in. We remark that the results remain valid for <italic>black box groups</italic> where group operations are performed by an oracle. The tools we introduce seem interesting in their own right. We define a new hierarchy of complexity classes <italic>AM</italic>(<italic>k</italic>) “just above <italic>NP</italic>”, introducing <italic>Arthur vs. Merlin games</italic>, the bounded-away version of Papdimitriou's <italic>Games against Nature</italic>. We prove that in spite of their analogy with the polynomial time hierarchy, the finite levels of this hierarchy collapse to <italic>AM=AM</italic>(2). Using a combinatorial lemma on finite groups [BE], we construct a game by which the nondeterministic player (Merlin) is able to convince the random player (Arthur) about the relation [<italic>G</italic>]=<italic>N</italic> provided Arthur trusts conclusions based on statistical evidence (such as a Slowly-Strassen type “proof” of primality). One can prove that <italic>AM</italic> consists precisely of those languages which belong to <italic>NP<supscrpt>B</supscrpt></italic> for almost every oracle <italic>B</italic>. Our hierarchy has an interesting, still unclarified relation to another hierarchy, obtained by removing the central ingredient from the <italic>User vs. Expert games</italic> of Goldwasser, Micali and Rackoff.
A field programmable analog array for CMOS continuous-time OTA-C filter applications

A programmable high-frequency operational transconductance amplifier (OTA) is proposed and analyzed. A general configurable analog block (CAB) is presented, which consists of the proposed programmable OTA, programmable capacitor and MOSFET switches. Using the CABs, the universal tunable and field programmable analog array (FPAA) can be constructed, which can realize many signal-processing functions, including filters. A tuning circuit is also discussed. The proposed OTA has been simulated and fabricated in CMOS technology. The results show that the OTA has the transconductance tunable/programmable in a wide range of 700 times and the -3-dB bandwidth larger than 20 MHz. A universal 5/spl times/8 CAB array has been fabricated. The chip has also been configured to realize OTA-C 60-kHz and 500-kHz bandpass filters based on ladder simulation and biquad cascade.
Multiple sites of adaptation lead to contrast encoding in the Drosophila olfactory system

Animals often encounter large increases in odor intensity that can persist for many seconds. These increases in the background odor are often accompanied by increases in the variance of the odor stimulus. Previous studies have shown that a persistent odor stimulus (odor background) results in a decrease in the response to brief odor pulses in the olfactory receptor neurons (ORNs). However, the contribution of adapting mechanisms beyond the ORNs is not clear. Thus, it is unclear how adaptive mechanisms are distributed within the olfactory circuit and what impact downstream adaptation may have on the encoding of odor stimuli. In this study, adaptation to the same odor stimulus is examined at multiple levels in the well studied and accessible Drosophila olfactory system. The responses of the ORNs are compared to the responses of the second order, projection neurons (PNs), directly connected to them. Adaptation in PN spike rate was found to be much greater than adaptation in the ORN spike rate. This greater adaptation allows PNs to encode odor contrast (ratio of pulse intensity to background intensity) with little ambiguity. Moreover, distinct neural mechanisms contribute to different aspects of adaptation; adaptation to the background odor is dominated by adaptation in spike generation in both ORNs and PNs, while adaptation to the odor pulse is dominated by changes within olfactory transduction and the glomerulus. These observations suggest that the olfactory system adapts at multiple sites to better match its response gain to stimulus statistics.
Foundational aspects of semantic web optimization

The goal of the semantic web is to make the information available on the web easier accessible. Its idea is to provide machine readable meta-data to enable the development of tools that support users in finding the relevant data. The goal of the thesis is to shed some light onto different foundational aspects of optimization tasks occurring in the field of the Semantic Web. Examples include the redundancy elimination in RDF data or static query analysis of (well-designed) SPARQL queries. Towards this goal, we already contributed several results.
9. References

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Using User-Generated Content when travelers make travel plans: A Theory of Planned Behavior perspective

User-Generated Content (UGC) such as online travel reviews written by tourists and posted to virtual communities are more used frequently to transmit travel-related information (Gretezel & Yoo). UGC is then helping travelers to make decisions on their travel plans. This study contributes to the further development of a theory of online consumer behavior by determining which dimensions of the theory of planned behavior (TPB) are most important in the UGC context in the travel industry. This study is utilizing TPB which is one of the most comprehensive intention-based models in the literature explaining the most variance in behavioral intention (Taylor & Todd, 1995). TPB has three independent determinants of intention: attitude toward behavior, subjective norm, and perceived behavior control (PBC). The aim of this paper is to examine the roles of attitude, subjective norm and perceived behavior control in respect of travelers' intention to use UGC when making travel plans. Further empirical research will be required to validate the proposed model.
Beehive: Erasure Codes for Fixing Multiple Failures in Distributed Storage Systems

In distributed storage systems, erasure codes have been increasingly deployed to tolerate server failures without loss of data. Traditional erasure codes, such as Reed-Solomon codes, suffer from a high volume of network transfer and disk I/O to recover unavailable data at failed storage servers. Typically, unavailable data at different failed storage servers in a distributed storage system are fixed separately. It has been shown that it is possible to reduce the volume of network transfer significantly by reconstructing data from multiple storage servers at the same time. However, there has been no construction of erasure codes to achieve it without imposing strict constraints on system parameters. In this paper, we propose Beehive codes, designed for optimizing the volume of network transfers to fix the data on multiple failed storage servers. Beehive codes can be constructed over a wide range of system parameters at code rate no more than 0.5, while incurring slightly more storage overhead than Reed-Solomon codes. To achieve the optimal storage overhead as Reed-Solomon codes, we further extend vanilla Beehive codes to MDS Beehive codes, which incurs near-optimal volumes of network transfers during reconstruction. We implement both Beehive and MDS Beehive Codes in C++ and evaluate their performance on Amazon EC2. Our evaluation results have clearly shown that the volume of both network transfers and disk I/O can be conserved by a substantial margin.
The use of Quality-Function Deployment ( QFD ) for customer-focused Product Development

In today’s competitive business environment, it is extremely important to offer customers exactly the products they want. Mass Customization promises to enable companies to offer a large variety of products while still being able to manage the complexity caused by this increased number of products. But offering a large range of variants does not necessarily mean increased profits, as many manufacturing companies had to notice in the early 1990ies. Therefore, valuebased product development methods are necessary to ascertain a product portfolio that optimally satisfies customer demands and at the same time restricts the number of products offered. This paper describes how the well-established product development and quality management method Quality Function Deployment (QFD) can be used to identify customer segments, and using the importance ascribed to certain customer requirements as input, the right product variants needed to satisfy the customer segments identified are defined.
Cognitive architecture for modelling human error in complex dynamic tasks

La litterature traitant des interactions homme-machine et des activites dans les systemes complexes et dynamiques a haut niveau de technologie, relevant de l'ingenierie cognitive, temoigne d'une substantielle discussion sur la notion d'erreur et de modelisation cognitive. Une raison a cela est que de bons modeles cognitifs pourraient etre utiles a la conception de systemes reconnaissant les erreurs, ou reduisant leur probabilite d'apparition. Ces modeles pourraient etre utiles lors de la realisation d'interfaces, de la conception de systemes de securite, de l'estimation de risques ou de la fiabilite, de la conception de cours sur les facteurs humains ou lors de l'analyse des causes d'accidents. Une moindre attention a ete portee a l'architecture a la base de tels modeles, meme si l'on cherche maintenant a faire en sorte que des architectures telles que ACT-R et soar puissent servir de support a la modelisation des tâches complexes. Chaque modele cognitif se fonde sur une architecture, qui peut etre cognitive. La nature cognitive de l'architecture limite la facilite de construction des modeles cognitifs, et, en particulier, dans la modelisation de l'erreur humaine. Une approche pour evaluer l'utilisation probable et la valeur d'une architecture pour modeliser les erreurs est de comparer les types d'erreurs observees lors de l'execution de tâches complexes reelles avec les mecanismes potentiellement fournis par l'architecture pour modeliser les erreurs. On presente ici une premiere etape de la comparaison entre trois approches differentes: celle dej. R. Anderson dans act-r, dej. Reason dans la Machine faillible (a la base du modele cosimo), et de M. J. Young dans l'Architecture cognitive Holon (hca). Des architectures telles que act-r ne sont pas specifiquement concues comme un cadre de modelisation du type d'erreur considere dans cet article, mais pourraient etre etendues afin de creer une architecture convenable. Des architectures telles que la Machine faillible de Reason, semblable a l'architecture a la base de cosmo, ont ete concues pour modeliser des erreurs mais la Machine faillible necessite de meilleures specifications, allant au-dela de celles fournies par cosimo. Des architectures telle hca semblent pouvoir supporter des modeles riches bien que parcimonieux, cependant ceci n'a pas ete valide. Dans tous les cas, on constate le besoin de modeliser des exemples reels d'erreurs lors de tâches dynamiques et complexes en utilisant les differentes architectures et de les tester en faisant des predictions, par exemple, sur les consequences d'une modification de l'interface, sur le comportement humain et ses erreurs.
Computing Semantic Relatedness using Wikipedia Taxonomy by Spreading Activation

Semantic relatedness means the degree of the nearness of two documents or two terms based on the sameness of their meaning or semantic contents. A method for computing semantic relatedness is crucial in the web mining applications such as search engine, recommendation systems and information retrieval systems, and also in the area of natural language processing. This paper proposes a new technique for measuring semantic relatedness between two terms. It uses Wikipedia as a source of structured world knowledge about the terms of interest while ontologies are used to retrieve the semantically related information in most systems. The proposed method used spreading activation approach over the taxonomy of Wikipedia categories to get the measures of semantic relatedness. Spreading activation strategy is a popular approach in associative retrieval. The proposed method is experienced with the benchmark dataset to show the comparison our approach with some existing approaches.
Analysis of Reliable Predictability based Motion Generation using RNNPB

Reliable predictability, which is tightly connected to consistency of environmental changes, is one of the main factors that determine human behaviors. As a constructive approach to understanding this mechanism, the authors have developed a method to generate autonomous object pushing motions based on consistency of object motions using a humanoid robot. The method consists of constructing a dynamics prediction model using Recurrent Neural Network with Parametric Bias (RNNPB), and motion searching based on an object consistency evaluation function using Steepest Descent Method. First, RNNPB is trained using the observed object dynamics and robot motion sequences, acquired during active sensing with objects. Next, the Steepest Descent Method is applied for searching the reliably predictable motion through the constructed dynamics model. Finally, the obtained motion is linked to the initial object image using a hierarchical neural network. The model inputs the object image outputting the reliably predictable robot motion which induces consistent object motions. The model was analyzed through two experiments, pushing cylindrical objects with a humanoid robot. The analysis has shown the method's effectivity and limitations to generate consistent object motions. I. I NTRODUCTION
LEAF: A System Level Leakage-Aware Floorplanner for SoCs

Process scaling and higher leakage power have resulted in increased power densities and elevated die temperatures. Due to the interdependence of temperature and leakage power, we observe that the floorplan has an impact on both the temperatures and the leakage of the IP-blocks in a system on chip (SoC). Hence, in this paper we propose a novel system level leakage aware floorplanner (LEAF) which optimizes floorplans for temperature-aware leakage power along with the traditional metrics of area and wire length. Our floorplanner takes a SoC netlist and the dynamic power profile of functional blocks to determine a placement while optimizing for temperature dependent leakage power, area, and wire length. To demonstrate the effectiveness of LEAF, we implemented our methodology on ten industrial SoC designs from Freescale Semiconductor Inc. and evaluated the trade-off between leakage power and area. We observed up to 190% difference in the leakage power between leakage-unaware and leakage aware floorplanning.
Collaborative Business Engineering: A Decade of Lessons from the Field

Business process reengineering (BPR) projects have been carried out for many years, with varying degrees of success. Two key reasons for failure are distinguished from the literature: insufficient stakeholder involvement and poor analyses of the business processes. The purpose of this paper is to present a decade of field experiences with collaborative BPR. Nine BPR projects were executed and analyzed in detail, leading to the identification of 87 themes regarding the efficiency and effectiveness of the project. These themes were organized into 12 categories of lessons learned that provide insight into the "best practices" and together informed the evolution of the collaborative business engineering (CBE) approach to BPR. The CBE approach combines a BPR process with collaboration and simulation modeling support to address the above-mentioned reasons for failure in BPR. The field experiences show that the CBE approach can be successfully applied for BPR projects in real life.