Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive precision in texture mapping

We introduce an adaptive, iterative technique for obtaining texture samples of arbitrary precision when synthesizing a computer-generated image. The technique is an improvement on the sum table texturing method. To motivate the technique we analyze the error properties of the sum-table method. Based on that analysis we propose using a combination of tables independently or together to obtain a better estimate, and analyze the error properties of such methods. We then propose a new technique for obtaining texture samples whose accuracy is a function of the texture and the image. As part of this technique we propose the use of an auxiliary table which contains local estimates of the texture variance. We show how the iteration of a given sample may be controlled by values from this table. We then analyze the error in this method, and present images which demonstrate the improvement.
The An Overview of Recent Trends in Incentive Pay Programs An Overview of Recent Trends in Incentive Pay Programs

This article examines recent trends and developments in an increasingly popular HR practice--incentive pay programs. In addition to highlighting major developments in recent empirical studies, this article also synthesizes recent research pertaining to general guidelines or strategies for design, implementation, and the utilization of incentive pay programs. Counter arguments pointing out potential pitfalls and precautions will also be discussed. The article concludes by offering some recommendations for future research.
Estratégias organizacionais, o difícil processo de tomada de decisão: caso de ensino da indústria têxtil

O caso tem por objetivo levar os alunos a vivenciar decisoes relacionadas ao processo de tomada de decisao organizacional, ao discutir as estrategias adotadas pela empresa com base no metodo classico de formulacao da estrategia descrito por Porter. O caso foi desenvolvido para ser usado em programas de pos-graduacao para discussao do processo de formulacao das estrategias; estrategias organizacionais e processo de reposicionamento da marca. Existe a possibilidade de adaptar as questoes de analise para ser usado por alunos da graduacao nas disciplinas de modelos de gestao. As informacoes descritas neste caso de ensino foram obtidas por meio de observacao participante, visita ao museu da empresa, e consulta a sites da empresa e da BM&FBovespa e entrevistas com funcionarios de diversos niveis hierarquicos da empresa. A proposta e fazer com que os estudantes se coloquem no lugar dos acionistas da empresa, para analisar as estrategias tomadas pela empresa, analisando cada estrategia dentro da roda de estrategia competitiva de Porter.
Implementation and Automatic Testing for Security Enhancement of Linux Based on Least Privilege

Nowadays, technologies of information security have been attached more and more importance to and it's a critical problem to take measures to ensure the reliability of related trustworthy software such as secure operating systems (SOSs). Thereafter, it's always necessary for such systems to be taken complete and rigorous security test and evaluation among development team and/or by third-party security certification organization. However, such software testing is usually time consuming, cost consuming and boresome and thus technologies of software testing automation have alluring application foreground in that field. In this paper, methods and technologies about how to test a SOS automatically are discussed in breadth and in depth at first. Then least privilege is studied and the corresponding modules of security enhancement are added to Linux based on Linux Kernel Modules (LKM). Finally, a prototype of automatic security testing as to such least privilege mechanism is implemented and the results are analyzed.
Major histocompatibility complex-specific recognition of Mls-1 is mediated by multiple elements of the T cell receptor

We have recently shown that recognition of the mouse mammary tumor virus 9-associated superantigen (vSAG-9) by murine V beta 17+ T cells is strongly influenced by the major histocompatibility complex (MHC) class II haplotype of the presenting cells, resulting in a form of MHC- restricted recognition. This finding was unexpected, because T cell recognition of another well-characterized retroviral superantigen, minor lymphocyte-stimulating antigen 1 (Mls-1), had been shown to be independent of the MHC haplotype of the presenting cell. To determine whether recognition of vSAG-9 and Mls-1 is fundamentally different, we undertook an extensive analysis of MHC haplotype influences on vSAG-9 and Mls-1 recognition by panels of T cell hybridomas. Our results show that, although most hybridomas recognized Mls-1 regardless of the MHC haplotype of the presenting cells, as previously described by others, some hybridomas exhibited unique patterns of MHC fine specificity. Thus, T cell recognition of vSAG-9 and Mls-1 is not fundamentally different, but the apparent differences can be explained in terms of frequency. The MHC fine specificity of individual Mls-1-reactive hybridomas was influenced by both V beta and non-V beta T cell receptor (TCR) elements. First, the influence of the V beta element was apparent from the observation that V beta 8.2+ hybridomas were significantly more MHC specific in their recognition of Mls-1 than V beta 8.1 hybridomas. Second, a role for the TCR alpha chain was implicated from the distinct patterns of fine specificity of Mls-1 reactivity among a panel of transgenic hybridomas that expressed an identical beta chain (V beta 8.1D beta 2J beta 2.3C beta 2). Sequence analysis revealed that junctional residues of the TCR alpha chain and/or V alpha/J alpha combinations influenced the MHC haplotype fine specificity for Mls-1. Third, D beta J beta influences were implicated, in that the transgenic hybridomas expressed distinctive patterns of Mls-1 fine specificity not represented among V beta 8.1+ nontransgenic hybridomas. The findings that T cell recognition of endogenous superantigen is MHC specific, and that this specificity correlates with non-V beta elements of the TCR, support the hypothesis that there is a direct interaction between the TCR and either polymorphic residues of the MHC class II molecule or haplotype-specific dominant peptides presented by class II.
An introduction to artificial neural networks

Artificial neural networks are algorithms which have been developed to tackle a range of computational problems. These range from modelling brain function to making predictions of time-dependent phenomena to solving hard (NP-complete) problems. In this introduction we describe a single, yet very important, type of network known as a feedforward network. This network is a mathematical model which can be trained to learn an arbitrarily complex relationship between a data and a parameter domain, so can be used to solve interpolation and classification problems. We discuss the structure, training and interpretation of these networks, and their implementation, taking the classification of stellar spectra as an example.
Efficient and Dynamic Algorithms for Alternating Büchi Games and Maximal End-Component Decomposition

The computation of the winning set for Büchi objectives in alternating games on graphs is a central problem in computer-aided verification with a large number of applications. The long-standing best known upper bound for solving the problem is Õ(n · m), where n is the number of vertices and m is the number of edges in the graph. We are the first to break the Õ(n · m) boundary by presenting a new technique that reduces the running time to O(n2). This bound also leads to O(n2)-time algorithms for computing the set of almost-sure winning vertices for Büchi objectives (1) in alternating games with probabilistic transitions (improving an earlier bound of Õ(n · m)), (2) in concurrent graph games with constant actions (improving an earlier bound of O(n3)), and (3) in Markov decision processes (improving for m>n4/3 an earlier bound of O(m · √m)). We then show how to maintain the winning set for Büchi objectives in alternating games under a sequence of edge insertions or a sequence of edge deletions in O(n) amortized time per operation. Our algorithms are the first dynamic algorithms for this problem. We then consider another core graph theoretic problem in verification of probabilistic systems, namely computing the maximal end-component decomposition of a graph. We present two improved static algorithms for the maximal end-component decomposition problem. Our first algorithm is an O(m · √m)-time algorithm, and our second algorithm is an O(n2)-time algorithm which is obtained using the same technique as for alternating Büchi games. Thus, we obtain an O(min {m · √m,n2})-time algorithm improving the long-standing O(n · m) time bound. Finally, we show how to maintain the maximal end-component decomposition of a graph under a sequence of edge insertions or a sequence of edge deletions in O(n) amortized time per edge deletion, and O(m) worst-case time per edge insertion. Again, our algorithms are the first dynamic algorithms for this problem.
Joint routing and controlled mobility for energy efficiency in Wireless Sensor Networks

Energy is a key concern in sensor networks as sensor nodes have a limited battery power and can not be replaced. In order to conserve energy efficiently, we proposed a sink movement scheme by traversing the whole network region to gather data from sensors within one or two hops along an Archimedean spiral trajectory. As the trajectory has a constant linear velocity and angular velocity, the sink can be controlled easily. We also optimized it by designing a simple routing protocol which can balance the energy consumption caused by the different distance from the sink trajectory. With the protocol, we can prolong the lifetime and reduce the delay by increasing the velocity of the sink. Simulation results show that our strategy can greatly prolong the network lifetime and balance energy consumption.
Usability Guidelines for Interactive Search in Direct Manipulation Systems

As AI systems make their way into the mainstream of interactive applications, usability becomes an increasingly important factor in their success. A wide range of user interface design guidelines have been developed for the direct manipulation and graphical user interface conventions of modern software. Unfortunately, it is not always clear how these should be applied to AI systems. This paper discusses a visualization assistant, an e-commerce simulation domain we have applied it to, and the guidelines we found relevant in the construction of its user interface. The goal of this paper is to explain how an interactive system can incorporates searchbased intelligent behavior while still respecting well-established rules for effective user interaction.
An Algorithm for Computing the Limit Points of the Quasi-component of a Regular Chain

For a regular chain $R$, we propose an algorithm which computes the (non-trivial) limit points of the quasi-component of $R$, that is, the set $\bar{W(R)} \setminus W(R)$. Our procedure relies on Puiseux series expansions and does not require to compute a system of generators of the saturated ideal of $R$. We focus on the case where this saturated ideal has dimension one and we discuss extensions of this work in higher dimensions. We provide experimental results illustrating the benefits of our algorithms.
AN Ω(D log(N/D)) LOWER BOUND FOR BROADCAST IN RADIO NETWORKS∗

We show that for any randomized broadcast protocol for radio networks, there exists a network in which the expected time to broadcast a message is Ω(D log(N/D)), where D is the diameter of the network and N is the number of nodes. This implies a tight lower bound of Ω(D log N) for any D ≤ N, where ε > 0 is any constant.
ℌ∞-suboptimal tracking control with integral action and load estimation applied on a Boost-converter/DC-motor combination

In this contribution, a ℌ∞-controller is devised for the tracking of a reference trajectory in a SISO-system. To this end, a ℌ∞ suboptimal set-point control concept for bilinear systems is adapted and generalized for tracking purposes resorting to the overall error dynamics of the respective timevarying system. The presented controller incorporates integral action on the angular shaft velocity and iISS (integral Input-to- State Stability) is guaranteed for the closed-loop system subject to non-zero disturbances. The integrator is to compensate for measurement noise, to compensate for load torque changes we introduce a load estimation scheme. Also iISS is shown for the closed-loop system under disturbances when completed with integrator and estimator. The approach is applied to a Boostconverter driven DC-motor, where the angular shaft velocity is the output to be tracked.
Operation optimization stand-alone microgrid using firefly algorithm considering lifetime characteristics of battery

Renewable energy sources and batteries are the important components to supply power on the stand-alone microgrid. Optimization of the stand-alone microgrid is needed to get the lowest energy generation const. The saving generation cost can be Renewable energy sources and batteries is an important component of the power supply stand-alone microgrid. Optimization of the stand-alone microgrid is needed to minimize energy generation cost. Saving cost can be obtained by choosing renewable energy sources as the power generation, such as photovoltaic (PV) and wind turbine (WT). In this paper, microgrid using PV, WT, and batteries as the main power supply of stand-alone microgrid. The diesel generator is used to supply power when PV, WT, and batteries can't supply power to load. Energy storage system management is the other option to optimization operation system. So, the life loss cost battery can be minimized. Based on simulation result, operation optimization using firefly algorithm (FA) can minimize generation cost and life loss cost battery.
Character D-modules via

The category of character D-modules is realized as Drinfeld center of the abelian monoidal category of Harish-Chandra bimodules. Tensor product of HarishChandra bimodules is related to convolution of D-modules via the long intertwining functor (Radon transform) by a result of [3]. Exactness property of the long intertwining functor on a cell subquotient of the Harish-Chandra bimodules category shows that the truncated convolution category of [21] can be realized as a subquotient of the category of Harish-Chandra bimodules. Together with the description of the truncated convolution category [5] this allows us to derive (under a mild technical assumption coming from [5]) classification of irreducible character sheaves over C obtained by Lusztig by a different method. We also give a simple description for the top cohomology of convolution of character sheaves over C in a given cell modulo smaller cells and relate the so-called Harish-Chandra functor to Verdier specialization in the De Concini-Procesi compactification.
Sleep disturbances and depression: risk relationships for subsequent depression and therapeutic implications

The majority of individuals with depression experience sleep disturbances. Depression is also over-represented among populations with a variety of sleep disorders. Although sleep disturbances are typical features of depression, such symptoms sometimes appear prior to an episode of depression. The bidirectional associations between sleep disturbance (especially insomnia) and depression increase the difficulty of differentiating cause-and-effect relationships between them. Longitudinal studies have consistently identified insomnia as a risk factor for the development of a new-onset or recurrent depression, and this association has been identified in young, middle-aged, and older adults. Studies have also observed that the combination of insomnia and depression influences the trajectory of depression, increasing episode severity and duration as well as relapse rates. Fortunately, recent studies have demonstrated that both pharmacological and nonpharmacological interventions for insomnia may favorably reduce and possibly prevent depression. Together, these findings suggest that sleep-related symptoms that are present before, during, andlor after a depressive episode are potentially modifiable factors that may play an important role in achieving and maintaining depression remission.
Design of Database Node Module in three-layered architecture for tele-operator

In this paper, our proposed software architecture for tele-operated systems such as planetary exploration rovers is introduced firstly. The architecture modularizes each function as a software module, makes advanced extendibility and flexible task management by connecting with a database via network and managing them, and, as a result, improves efficiency in development and operation stages of systems. Those functions of the architecture is realized with DNM (Database Node Module), therefore we discuss and design it. DNMs are databases to which all the functional modules on system are connected, and they require functions, which manage the connections of modules and control data flows and execution-sequences. The management function of module connections improves the system maintenancebility by applying a virtual attachment facility. The other function performing the data flows of modules is realized by a shared memory, and it is also in charge of improvement of communication speed and visualizing communication. Its system performance with DNM was evaluated with a transmission speed and a system load by a simulation, and stability assessment was proceeded by using an actual robot. According to experimental results, DNM and its system showed us their performance designed and required in this paper, and the validities of the architecture and DNM have been indicated.
Multi-Objective Optimization for Ensemble of Models in Software Reliability Prediction

Software reliability models are very useful to estimate the probability of the software fail along the time. Several different models have been proposed to predict the software reliability growth models (SRGM) however; none of them has proven to perform well considering different project characteristics. The variability of predictive accuracy seems mainly due to the unrealistic assumptions in each model, there is no single model yet available has been shown to be sufficiently trustworthy in most or all applications. Genetic Algorithms can proposed the solution by overcome the uncertainties in the modeling. This is dependent on the successful software runs by combining multiple models using multiple objective function to achieve the best generalization performance where. The objectives are conflicting and no design exists which can be considered best with respect to all objectives. In this paper, experiments were conducted to confirm these hypotheses. Then evaluating the predictive capability of the ensemble of models optimized using multi-objective GA has been calculated. Finally, the results were compared with traditional models.
Track-to-track association and bias removal

This paper develops methods for associating two sets of sensor tracks in the presence of missing tracks and translation bias. Key results include 1) extension of the maximum A Posteriori probability method of matching tracks to use feature information as well as kinematic information; 2) translation bias removal techniques that are computationally tractable for large numbers of tracks, and effective in the presence of missing tracks. These methods were evaluated by Monte Carlo simulation. The experimental results indicate that the maximum A Posteriori probability method with its adaptive threshold achieves close to its best performance for matching tracks without an additional threshold adjustment.
The scaling of the X-ray variability with black hole mass in active galactic nuclei

The relation between the 2-10 keV, long-term, excess variance and active galactic nuclei (AGN) black hole mass is considered in this work. A significant anticorrelation is found between these two quantities in the sense that the excess variance decreases with increasing black hole mass. This anticorrelation is consistent with the hypothesis that the 2-10 keV power spectrum in AGN follows a power law of slope -2 at high frequencies. It then flattens to a slope of -1 below a break frequency, ν hfb , until a second break frequency, ν lfb , below which it flattens to a slope of 0. The ratio ν hfb /ν lfb is equal to 10-30, similar to the ratio of the respective frequencies in Cyg X-1. The power spectrum amplitude in the (frequency x power) space does not depend on black hole mass. Instead, it is roughly equal to 0.02 in all objects. The high-frequency break decreases with increasing black hole mass according to the relation ν hfb = 1.5 x 10 -6 /(M/ 10 7 M ○. ) Hz, in the case of 'classical' Seyfert 1 galaxies. The excess variance of NGC 4051, a narrow-line Seyfert 1 object, is larger than is expected for its black hole mass and X-ray luminosity. This can be explained if its ν hfb is 20 times larger than the value expected in the case of a 'classical' Seyfert 1 with the same black hole mass. Finally, the excess variance versus X-ray luminosity correlation is a by-product of the excess variance versus black hole mass correlation, with AGN accreting at ∼ 0.1-0.15 times the Eddington limit. These results are consistent with recent results from the power spectral analysis of AGN. However, as they are based on data from a few objects only, further investigation is necessary to confirm that there is indeed a 'universal' power spectrum shape in AGN (in the sense that the value of the power spectrum parameters of most AGN will be distributed around the 'canonical' slope, and amplitude values listed above). One way to achieve this is to determine the excess variance versus black hole relation more accurately, using data from many more objects. This will be possible in the near future, because it is easier to measure the excess variance of archival light curves than to estimate their power spectrum. The excess variance versus black hole relation can therefore play an important role in the study of the X-ray variability scaling with black hole mass in AGN.
Bi-ocularidad, el funcionamiento de la mente en el psicoanálisis

Con el uso del material clínico el autor discute la importancia de un modo de atención ‘bi-ocular’, un polo de lo que descansa ene el proceso psíquico de reverie y que el otro sobre ‘analizar’. Esto es necesario para promover el desarrollo de un espacio psíquico en el cual las experiencias estaban ‘en la sombra’ o no representadas, pueden tener éxito y que se les de forma primero con ilustraciones y luego ideacionalmente. Esto requiere permanecer y promover la ambigüedad de los diferentes tiempos y espacios sin colapsarlas en lo claro, lógico y explicativo. Requiere que el psicoanalista haga lugar para lo que es ‘el otro’, otro que solo sea más que aparentemente aquí y ahora y otro que más que solo’ tú y yo’, manteniendo el ‘fuego’ analítico en una situación en la que no hay ‘ningún modelo en la vida real’, un lugar principalmente adaptado a lo que no es aparente.
The effect of spatial characteristics on inhibition of return in 6-month-old infants

MONTH-OLD INFANTS by KRISZTINA VARGA (Under the Direction of Janet E. Frick) ABSTRACT Inhibition of return (IOR) is the tendency to reduce attention to a previously cued location. Infant studies have found that IOR develops between the ages of four and six months of age. The methodology used in infant studies is comparable to those used in studying IOR in adults. However, recent adult research has found that the spatial characteristics of the cues and targets play a role in observing inhibition. This study examined these effects on IOR in 6month-old infants. The results replicated previous findings of IOR in 6-month-olds and also found differences in RT to stimuli that differed in spatial characteristics in some conditions. The findings of this study indicate that future research needs to be implemented to further understand the effects of stimuli on IOR in young infants.