Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust model for spot virtual machine bidding in the cloud market using information gap decision theory (IGDT)

: The spot market is one of the most common cloud markets where cloud providers, such as Amazon EC2, rent their surplus computing resources at lower prices in the form of spot virtual machines (SVMs). In this market, which is often managed through an auction mechanism, users seek optimal bidding strategies for renting SVMs to minimize cost and risk. Uncertainty in the price of SVMs and their low availability/reliability is a challenging issue to bid on the user side. In this paper, we present a robust model for minimizing the cost of executing tasks by considering the uncertainty of the price of SVMs based on the Information Gap Decision Theory (IGDT). It evaluates the risk-aversion and the risk-seeker nature of the user’s bidding strategy and measures the cost of risk/immunity. The main advantage of this method is that it formulates user decisions without the need for any presumption about the price distribution of SVMs. With this decision-support system, users can rely on the predicted confidence intervals to make the optimal bid for future time slots according to the selected risk level. The results are compared with Monte Carlo simulations and a scenario-based approach to evaluate the effectiveness of the proposed IGDT-based model. Evaluation results based on historical Amazon EC2 prices confirm the eﬀiciency of the proposed method to handle the uncertain nature of the price of SVMs in terms of significant criteria such as robustness cost, opportunity cost, uncertainty budget, and execution time.
High-resolution spectroscopic observations of two chemically peculiar metal-poor stars: HD 10613 and BD+04 ◦ 2466

Aims. We determined the atmospheric parameters and abundance pattern of two chemically peculiar metal-poor stars: HD 10613 and BD+04 ◦ 2466 in order to better understand their evolutionary state and the nature of the s-element enhancement of these stars. Methods. We used high resolution optical spectroscopy. Atmospheric parameters and abundances were determined in the localthermodynamic-equilibrium model atmospheres of Kurucz using the spectral analysis code MOOG. Results. We conclude that HD 10613 is another metal-poor barium star with C/O = 0.52 and [Fe/H] = −0.82, while BD+04 ◦ 2466 is a CH star with C/O = 3.6 and [Fe/H] = −1.92 rather than a metal-deficient barium star as it was previously classified. BD+04 ◦ 2466 appears to be enriched in lead with [Pb/Ce] =+ 0.85 and [Pb/La] =+ 0.72. For BD+04 ◦ 2466 the abundance of lead is in agreement with predictions from AGB models. Due to the low luminosity of these two stars, their observed s-process overabundance is better explained by mass-transfer in the past from an AGB star.
A 10-Gb/s Inductorless Low-Power TIA With a 400-fF Low-Speed Avalanche Photodiode Realized in CMOS Process

Compared with SiGe technology, the limits of low transition frequency and low transconductance per unit current of CMOS technology result in poor noise, narrow bandwidth, and high power consumption in high-speed transimpedance amplifiers. The aforementioned issues are further exacerbated while using a low-speed low-cost photodiode. In this study, an equalization technique is proposed to increase the feedback resistance <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {R_{F}}$ </tex-math></inline-formula>, achieving low noise and bandwidth extension of the chip. A novel inductorless bandwidth extension technique is proposed to increase the bandwidth of high-speed channel by 37.5%. In addition, a new current reuse technique is proposed to inject the output stage’s tail current into the input stage to achieve a high gain, saving power consumption by 20%. We achieve 10-Gb/s operation with a 400-fF avalanche photodiode (APD) using 65-nm CMOS technology. The bandwidth is 6.8 GHz, the transimpedance gain is 66 dB<inline-formula> <tex-math notation="LaTeX">$\boldsymbol{\Omega }$ </tex-math></inline-formula>, the average input-referred noise current is 11.9 pA/<inline-formula> <tex-math notation="LaTeX">$\surd $ </tex-math></inline-formula>Hz, and the average sensitivity is −22.4 dBm at a BER of 1e−12. The SF-TIA chip takes up 0.56 mm2 and consumes 26 mA from a 3.3-V supply.
Study of Quantum genetic algorithm based on mutative scale chaotic optimization

Aiming at the trouble of easy getting into local minimum in quantum genetic algorithm, this paper presents a new hybrid quantum genetic algorithm. Using the method of mutative scale chaos optimization strategy, chaotic search for optimization is implemented to the colony which has been processed one time with quantum genetic algorithm, which can lead rapid evolution of the colony. The method has advantages such as high searching efficiency, good computing precision and being convenient to use, etc. The test of typical function shows the performance of this kind of method is better than quantum genetic algorithm and genetic algorithm.
The influence of extinction coefficient on transmission in binary multilayer

Purpose: The influence of the extinction coefficient for transmission, reflectance and absorption in multilayer binary. Reps cluster was equal to 7 It was built of two types of materials. First was a NaCl equivalent with a refractive index described by nA=1.544-ik , and as second was GaAs lossless metamaterial equivalent Design/methodology/approach: Research was carried out using the map of: transmitting, reflectance and absorption of the electromagnetic wave. Maps determined using the matrix method. Findings: It is shown that the higher the extinction coefficient, which is responsible for the absorption of electromagnetic waves, decreases the transmittance and reflectance of the multilayer system at the same time increasing its absorption. Research limitations/implications: Would be a reasonable correlation between the results of the transmission, reflectance and absorption obtained using numerical methods with with experiment. Practical implications: Taking into account the extinction coefficient allows for a better representation of the real multilayer structures. Quasi one-dimensional superlattices can be used as filters or multiplexers electromagnetic waves. Originality/value: In the literature the most frequently analyzed lossless structure. Taking into account the extinction coefficient allows for better study the properties of the tested materials.
Linear approximations for factored markov decision processes

A Markov Decision Process (MDP) is a model employed to describe problems in which a decision must be made at each one of several stages, while receiving feedback from the environment. This type of model has been extensively studied in the operations research community and fundamental algorithms have been developed to solve associated problems. However, these algorithms are quite inefficient for very large problems, leading to a need for alternatives; since MDP problems are provably hard on compressed representations, one becomes content even with algorithms which may perform well at least on specific classes of problems. The class of problems we deal with in this thesis allows succinct representations for the MDP as a dynamic Bayes network, and for its solution as a weighted combination of basis functions. We develop novel algorithms for producing, improving, and calculating the error of approximate solutions for MDPs using a compressed representation. Specifically, we develop an efficient branch-and-bound algorithm for computing the Bellman error of the compact approximate solution regardless of its provenance. We introduce an efficient direct linear programming algorithm which, using incremental constraints generation, achieves run times significantly smaller than existing approximate algorithms without much loss of accuracy. We also show a novel direct linear programming algorithm which, instead of employing constraints generation, transforms the exponentially many constraints into a compact form more amenable for tractable solutions. In spite of its perceived importance, the efficient optimization of the Bellman error towards an approximate MDP solution has eluded current algorithms; to this end we propose a novel branch-and-bound approximate policy iteration algorithm which makes direct use of our branch-and-bound method for computing the Bellman error. We further investigate another procedure for obtaining an approximate solution based on the dual of the direct, approximate linear programming formulation for solving MDPs. To address both the loss of accuracy resulting from the direct, approximate linear program solution and the question of where basis functions come from we also develop a principled system able not only to produce the initial set of basis functions, but also able to augment it with new basis functions automatically generated such that the approximation error decreases according to the user's requirements and time limitations.
Analysing the use of history of mathematics through MKT†

In this article, we analyse three ‘classical’ cases of using history of mathematics in teacher training and reinterpret them using the framework of mathematical knowledge for teaching (MKT). We continue with a discussion of the potential benefits of applying MKT as a framework for discussion in research related to the use of history in mathematics education. MKT serves as an example of a framework from general mathematics education research which has something to offer in this respect. We argue that the MKT framework provides a powerful language to communicate results from research on the uses of history of mathematics to researchers in other areas of mathematics education research.
Absolutely convergent multiple Fourier series and multiplicative Zygmund classes of functions

We study the smoothness properties of a complex-valued function f of several variables with absolutely convergent Fourier series. We prove sufficient conditions in terms of the Fourier coefficients of f in order that f belong to one of the multiplicative Zygmund classes Zyg(α1, α2,…,αN) and zyg(α1, α2,…,αN) for some α1, α2,…,αN > 0. These Zygmund classes of functions are defined in terms of the multiple difference operator of second order in each variable. The conditions given by us are not only sufficient, but also necessary in the case when the Fourier coefficients are nonnegative.
A proximity algorithm accelerated by Gauss–Seidel iterations for L1/TV denoising models

Our goal in this paper is to improve the computational performance of the proximity algorithms for the L1/TV denoising model. This leads us to a new characterization of all solutions to the L1/TV model via fixed-point equations expressed in terms of the proximity operators. Based upon this observation we develop an algorithm for solving the model and establish its convergence. Furthermore, we demonstrate that the proposed algorithm can be accelerated through the use of the componentwise Gauss–Seidel iteration so that the CPU time consumed is significantly reduced. Numerical experiments using the proposed algorithm for impulsive noise removal are included, with a comparison to three recently developed algorithms. The numerical results show that while the proposed algorithm enjoys a high quality of the restored images, as the other three known algorithms do, it performs significantly better in terms of computational efficiency measured in the CPU time consumed.
Detection and Tracking of Vehicles Using License Plate Recognition

The density of vehicles on roads has increased manifold over the last few decades. A seamless system to detect and track a particular vehicle can solve many problems, like traffic congestion, etc. This paper proposes the use of real-time data taken from closed-circuit televisions to detect and track the movements of vehicles. The feature extraction and classification are completely done by the process of faster RCNN (regional convolutional neural networks). The core work is based on region proposal networks. CNN furthers the generation of features; classification is done separately, but it is aided by RCNN, which includes deep learning as well as training the neural network. This is used along with the Kanade Lukas Tomasi algorithm to tack the desired features extracted. This method is simulated on MATLAB software.
Use of Pseudoadiabatic Adjustment of Turbulence for a Simplified Nighttime Stratocumulus Case: A One-Dimensional Study

Abstract A turbulence–condensation parameterization scheme for a stratocumulus-topped planetary boundary layer that may be applied in mesoscale numerical weather prediction models is presented in this paper. Due to the condensation closure, conservative variables such as liquid water potential temperature and total water mixing ratio are not suitable to use and an approach referred to as pseudoadiabatic adjustment of turbulent fluxes (within the cloud) is suggested as a replacement. This approach is investigated and compared with large eddy simulation (LES) results for a simplified stratocumulus case driven mainly by cloud-top radiative cooling. It is shown that the results for two vertical resolutions, 25 m and 100 m, are similar to LES data and both a maximum buoyancy flux at the cloud top and a quasi-linear total water flux are produced. The discrepancies between the runs with 100- and 25-m resolution are mainly related to the entrainment process, which is much weaker in the former run. A diurnal cycle.
Charge Ordering in the Geometrically Frustrated Spinel AlV2O4

We have found that spinel AlV 2 O 4 shows a phase transition at ∼700 K with anomalies of transport and magnetic properties. It is clarified that this corresponds to a charge-ordering transition, where the V 2.5+ ions are separated into three V 2.5-δ ions and one V 2.5+3δ ion. This three-one type of charge ordering, which is coupled with rhombohedral distortion along the (111) axis, reduces the high degeneracy of ground states inherent in this spinel structure, and thus can be understood in terms of “charge frustration. ”
Output regulation of linear plants with actuators subject to amplitude and rate constraints

We consider semi-global stabilization and output regulation problems via state and measurements feedback for linear plants (both continuous-time and discrete-time) with actuators subject to amplitude and rate saturation. In our approach, the actuator constraints are modelled as an operator and is incorporated in the controller so that the control signal does not overload the actuators. Both the problem formulation and the analysis is done in the functional differential equation framework.
Automatic Selection of Methods for Solving Stiff and Nonstiff Systems of Ordinary Differential Equations

This paper describes a scheme for automatically determining whether a problem can be solved more efficiently using a class of methods suited for nonstiff problems or a class of methods designed for stiff problems. The technique uses information that is available at the end of each step in the integration for making the decision between the two types of methods. If a problem changes character in the interval of integration, the solver automatically switches to the class of methods which is likely to be most efficient for that part of the problem. Test results, using a modified version of the LSODE package, indicate that many problems can be solved more efficiently using this scheme than with a single class of methods, and that the overhead of choosing the most efficient methods is relatively small.
The implication of CSR on the performance of SMEs in the context of a developing economy

While corporate social responsibility (CSR) has been extensively explored from the standpoint of large corporations and developed economies, smaller businesses and developing economies have received little attention. Small and medium-sized enterprises (SMEs) continue to be the backbone of most economies, significantly accounting for a major share in economic value creation. This implies that the contribution of SMEs in achieving sustainable development is therefore critical. The study seeks to add to the limited literature by investigating the implication of socially responsible behavior on the performance of SMEs in Nigeria. Corporate reputation, profit maximization and management efficiency are dependent variables used as proxies for performance measurement. A well-structured questionnaire was administered to 63 Nigerian SMEs. The study adopted a structural equation model using SmartPLS for the data analysis. Findings show a significant relationship between corporate social responsibility and the three determinants of firm performance (management efficiency, profit maximization and corporate reputation). This study has implications for owners/managers of SMEs who are keen on improving performance by leveraging on socially responsible behaviour through the development, implementation and communication of a sustainable and acceptable CSR initiative. Recommendations and suggestions for further investigations are made.
X-ray, optical, and infrared luminosity correlations in radio-quiet quasars

Published UV, optical, and infrared photometry for a sample of X-ray observed, radio-quiet quasars are analyzed. The criteria used to select the sample are discussed, and the general shape of the IR/optical continuum is examined. Correlations among the various wavebands are analyzed, and the implications for the empirical shape of the X-ray-to-infrared continuum in quasars and of possible energy generation mechanisms are considered. 65 references.
Application of smart visualisation in the analysis of Hungarian Agriculture ICT

Agriculture has a certain specialty in information technology, and the application of new ICT technologies is inevitable. First, we discuss the idea behind data, concepts such as data storytelling, types and proper use of visualisation. There are several well-known visualisation types, but we would like to point out some AI (Artificial Intelligence) based ones (decomposition tree, treemap, Q&A). Our institute has prepared a survey to investigate ICT usage and attitudes of companies in the agri-food sector. The importance of business processes that can be supported by ICT had to be evaluated by the companies. In this study, we evaluated the importance of some ICT indicators. To ensure the use of the mentioned intelligent visualisation, we present some examples from our institute's questionnaire on ICT use in agriculture. We found the smart visualisation usable and the idea of smart dashboards seems to be usable in practice.
Dimension-Specific Shared Autonomy for Handling Disagreement in Telemanipulation

One of the fundamental questions in shared control is how to allocate control power to the human and robot effectively. Conventional arbitration policies often define a uniform singular scalar for all 6 DOFs to blend human input and robot assistance. However, this singular scalar over-dominates some dimensions of the inputs and provides insufficient assistance in other dimensions. Thus, current shared control can support simple telemanipulation tasks such as pushing, pressing, and simple positional control but is limited in tasks with more DOFs like rotational motion. A dimension-specific arbitration policy is developed to customize the control arbitration along each DOF to fill the gap. It looks at whether the robotic assistance is too timid or aggressive along each DOF and determines the arbitration magnitude according to disagreement levels of control allocation and the user's willingness to accept assistance. The user's willingness is estimated from a feedback psychology model. The method has higher similarity and ratio of agreement between the human and robot (lower over-dominance) over existing methods and, simultaneously, improves the task performance. This arbitration strategy is expected to increase the adoption of teleoperation for object manipulation.
M2STaR: A Multimode Spatio-Temporal Redundancy Design for Fault-Tolerant Coarse-Grained Reconfigurable Architectures

Coarse-grained reconfigurable architectures (CGRAs) can provide both energy efficiency and performance for embedded systems, and thus they are increasingly deployed in the areas of aerospace, automotive engineering, and security where reliability is also a main criterion. However, the state-of-the-art fault-tolerant strategies for CGRAs apply either temporal or spatial scheme, including redundancy, periodic detection, workload balancing, and reconfiguration, failing to exploit the feature of dynamic and partial reconfiguration of CGRAs. Also, vulnerable judging circuits and inflexible mode shifting bottleneck the reliability design of fault-tolerant CGRAs. This article proposes a novel multimode fault-tolerant framework for CGRAs, which combines spatial-redundant data paths with temporal-redundant voters and thus reduces the vulnerable judging circuits while balancing the performance and reliability. This framework can also enable a changing reliability level at runtime via an online configuration transformation method based on precompiled patterns. Within the proposed framework, we systematically searched the design space spanning various combinations of the mainstream schemes with a Markov process model to compare the effectiveness and accordingly selected five points as available modes in our design after comprehensive consideration of fault tolerance and time overhead on CGRA. The framework is comprehensively evaluated on a cycle-accurate CGRA simulator, considering both permanent and transient faults. The experimental results show that the fault coverage rate of single transient faults or permanent faults has increased from 71.74% to 93.84%, which means the fault tolerance of the system has been increased by 31.03% compared with the state-of-the-art methods. There is also a great improvement in mean-time-to-failure (MTTF) and reconfiguration latency over baseline designs.
Probabilistic deletion of copies of linearly independent quantum states

We show that each of two copies of the nonorthogonal states randomly selected from a certain set S can be probabilistically deleted by a general unitary-reduction operation if and only if the states are linearly independent. We derive a tight bound on the best possible deleting efficiencies. These results for 2-->1 probabilistic deleting are also generalized into the case of N-->M deleting (N,M positive integers and N>M).
Activation of Ethanol Transformation on Copper-Containing SBA-15 and MnSBA-15 Catalysts by the Presence of Oxygen in the Reaction Mixture

The aim of this study was to get insight into the pathway of the acetaldehyde formation from ethanol (the rate-limiting step in the production of 1,3-butadiene) on Cu-SBA-15 and Cu-MnSBA-15 mesoporous molecular sieves. Physicochemical properties of the catalysts were investigated by XRD, N2 ads/des, Uv-vis, XPS, EPR, pyridine adsorption combined with FTIR, 2-propanol decomposition and 2,5-hexanedione cyclization and dehydration test reactions. Ethanol dehydrogenation to acetaldehyde (without and with oxygen) was studied in a flow system using the FTIR technique. In particular, the effect of Lewis acid and basic (Lewis and BrØnsted) sites, and the oxygen presence in the gas reaction mixture with ethanol on the activity and selectivity of copper catalysts, was assessed and discussed. Two different reaction pathways have been proposed depending on the reaction temperature and the presence or absence of oxygen in the flow of the reagents (via ethoxy intermediate way at 593 K, in ethanol flow, or ethoxide intermediate way at 473 K in the presence of ethanol and oxygen in the reaction mixture).