Miracle-dz/UniFAR-FTUs huggingface dataset:
Buoyancy-induced convection from a pair of heated and cooled horizontal circular cylinders inside an adiabatic tilted cavity filled with alumina/water nanofluids

Purpose This paper aims to investigate numerically buoyancy-induced convection from a pair of differentially heated horizontal circular cylinders set side by side in a nanofluid-filled adiabatic square enclosure, inclined with respect to gravity so that the heated cylinder is located below the cooled one, using a two-phase model based on the double-diffusive approach assuming that the Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase. Design/methodology/approach The system of the governing equations of continuity, momentum and energy for the nanofluid, and continuity for the nanoparticles, is solved by a computational code based on the SIMPLE-C algorithm. Numerical simulations are performed for Al2O3 + H2O nanofluids using the average volume fraction of the suspended solid phase, the tilting angle of the enclosure, the nanoparticle size, the average nanofluid temperature and the inter-cylinder spacing, as independent variables. Findings The main results obtained may be summarized as follows: at high temperatures, the nanofluid heat transfer performance relative to that of the pure base liquid increases with increasing the average volume fraction of the suspended solid phase, whereas at low temperatures it has a peak at an optimal particle loading; the relative heat transfer performance of the nanofluid has a peak at an optimal tilting angle of the enclosure; the relative heat transfer performance of the nanofluid increases notably as the average temperature is increased, and just moderately as inter-cylinder spacing is increased and the nanoparticle size is decreased. Originality/value The two-phase computational code used in the present study incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity and the coefficient of thermophoretic diffusion, all based on a high number of literature experimental data.
Sliding mode control of quantum systems

This paper proposes a new robust control method for quantum systems with uncertainties involving sliding mode control (SMC). SMC is a widely used approach in classical control theory and industrial applications. We show that SMC is also a useful method for robust control of quantum systems. In this paper, we define two specific classes of sliding modes (i.e. eigenstates and state subspaces) and propose two novel methods combining unitary control and periodic projective measurements for the design of quantum SMC systems. Two examples including a two-level system and a three-level system are presented to demonstrate the proposed SMC method. One of the main features of the proposed method is that the designed control laws can guarantee the desired control performance in the presence of uncertainties in the system Hamiltonian. This SMC approach provides a useful control theoretic tool for robust quantum information processing with uncertainties.
Semi-analytical full-wave model for simulations of scans in optical coherence tomography with accounting for beam focusing and the motion of scatterers

A full-wave model for simulating images in spectral-domain optical coherence tomography (OCT) with rigorous accounting for the beam-focusing effects is developed. Due to the analytical description of beam focusing, the model is computationally rather efficient. It also uses a rigorous numerical summation of the contributions of the localized sub-resolution scatterers, accounting for variations in the phase-amplitude parameters of the incident and backscattered optical waves, with a subsequent integration of the latter over the objective aperture. In the limit of a weakly focused beam, the developed model has allowed for the validatation of the earlier proposed simplified model with a constant-radius beam. It is shown that, for weakly focused beams, utilization of the computationally more efficient simplified model is quite sufficient, especially when simulation of numerous OCT scans in tissues with moving scatterers is necessary. The relevant examples related to the OCT imaging of spatially inhomogeneous strains are given. When the application of strongly focused beams is indispensable to obtain ultimately high resolution in OCT scans, the developed rigorous model for strongly focused beams offers convenient possibilities for developing methods of numerical refocusing. Possibilities to ensure uniform, close-to-maximal resolution not only in the focus waist, but over the entire imaged depth range, are demonstrated in simulations based on the developed model.
Accelerating CNN’s forward process on mobile GPU using OpenCL

The convolution neural network (CNN) is becoming more and more powerful in many areas such as image classification and speech recognition. Some projects begin to apply it on mobile phones, but often need plenty of time due to the huge amount of computation. This paper uses a deep learning framework named MXNet to realize the forward process on the mobile phone. In order to lower the time it costs, we focus on how to use the other computing device on the chip—the mobile GPU. We choose the OpenCL to offload the most time consuming layer in the CNN—convolution layer to the GPU. Besides that, this paper makes several improvements to achieve better performance and finally the experimental results demonstrate that the forward process only takes half the time in our algorithm. To the best of the authors’ knowledge, this work is the first published implantation of CNN accelerating on mobile GPU.
First order Quantum Hall Transitions in Hofstadter Butterfly in the Honeycomb Lattice

We analyze the effects of nearest neighbor repulsive interactions in the Hofstadter system in a honeycomb lattice. At low fillings, we show that, as the interaction strength is increased there are two first order transitions, a Landau transition with translational and rotational symmetries broken, followed by a topological transition with a jump in the quantized Hall conductivity. We therefore predict that in physical realizations where the interaction effects are strong, there would be translation symmetry broken states with quantized Hall conductivities that differ from those predicted by the non-interacting theory.
Fault-tolerant controller design with fault estimation capability for a class of nonlinear systems using generalized Takagi-Sugeno fuzzy model

In this paper, a new design approach to construct a fault-tolerant controller (FTC) with fault estimation capability is proposed using a generalized Takagi-Sugeno (T-S) fuzzy model for a class of nonlinear systems in the presence of actuator faults and unknown disturbances. The generalized T-S fuzzy model consists of some local models with multiplicative nonlinear terms that satisfy Lipschitz condition. Besides covering a very wide range of nonlinear systems with a smaller number of local rules in comparison with the conventional T-S fuzzy model and hence having less computational burden, the existence of the multiplicative nonlinear term solves the uncontrollability issues that the other generalized T-S fuzzy models with additive nonlinear terms dealt with. A state/fault observer designed for the considered generalized T-S fuzzy model and then, a dynamic FTC law based on the estimated fault information is proposed and sufficient design conditions are given in terms of linear matrix inequalities (LMIs). It can be shown that the number of LMIs are less than that of previously proposed methods and then feasibility of our method is more likely. The effectiveness of the proposed FTC approach is verified using a nonlinear mass-spring-damper system.
Simulasi Deteksi Sinyal Radar Pada simulator ESM Menggunakan Metode Kalman Filter Pada ESM (Electronic Support Measured)

Radar adalah sistem elektromagnetik untuk mendeteksi dan menentukan lokasi suatu benda seperti pesawat terbang, kapal, pesawat ruang angkasa, kendaraan, orang, dan lingkungan alam. beroperasi dengan memancarkan energi dan mendeteksi sinyal yang dipantulkan dari obyek, atau target. Dalam peperangan elektronik banyak dikembangkan system pendeteksian sinyal radar untuk mengklasifikasikan jenis radar. Salah satu system untuk deteksi sinyal radar adalah system ESM (Elctronic Support Measured) yang berfungsi untuk deinterleaving sinyal radar yang berasal dari sumber berbeda. Sinyal yang dipancarkan oleh banyak radar akan diterima pada penerima yaitu ESM dalam keadaan yang saling tumpang tindih (interleaving) sesuai dengan niali TOA masing-masing radar. Sehingga diperlukan proses deinterleaving untuk memisahkan kembali sinyal yang tercampur, sehingga dapat diketahui jenis radar tersebut. Salah satu Parameter yang banyak digunakan untuk proses deteksi radar adalah PRI (pulse repetition interval). PRI pada radar terdiri dari berbagai macam yaitu PRI constant, PRI jitter dan PRI Stagger. Untuk jenis PRI constant dan jitter disimulasikan menggunakan metode PRI transform dan improvement PRI transform, sedangkan untuk PRI stagger digunakan metode kalman Filter. Performa dari metode yang diusulkan dievaluasi menggunakan matlab.
A Filled Flatten Function Method Based on Basin Deepening and Adaptive Initial Point for Global Optimization

Currently, there are four drawbacks for filled function methods: (1) too many local optimal solutions result in huge difficulty to search global optimal solutions; (2) difficult to control the parameter(s); (3) difficult to determine the initial point for minimization of filled function; (4) the shallow basins will affect the solution precision during the minimization of the filled function. To overcome these drawbacks, in this paper, we adopt a flatten function to eliminate many local optimal solutions first, and then a new filled function with one parameter is proposed, and its parameter is easy to control. Furthermore, we propose an efficient method for determining initial point of the filled function by using adaptive step size. Moreover, when some basins of the filled function are shallow ones, it will result in inefficiency of searching these basins during the minimization of the filled function. To tackle this issue and make the search for global optimal solutions much easier, we propose a strategy of basin deepening. By integrating these schemes, we propose a new efficient filled flatten function method. Numerical results indicate the efficiency and effectiveness of the proposed filled function methods.
Physical Laws and Effects

By C. F. Hix, Jr., and R. P. Alley New York : John Wiley & Sons, Inc.; London: Chapman & Hall Ltd. Pp. 291. Price 64s. The deliberately cryptic descriptions given in this book, one of a series written by (American) General Electric authors, are intended as a quick reference source for engineers and scientists, and the value of this useful compilation is enhanced by its being indexed alphabetically by names, physical quantities involved, and fields of science. In the opening chapter Mr. Hix suggests various ways in which the book can be used as " a practical part of the engineering approach to problems. "
Collecting and utilising crowdsourced data for numerical weather prediction: Propositions from the meeting held in Copenhagen, 4–5 December 2018

In December 2018, the Danish Meteorological Institute organised an international meeting on the subject of crowdsourced data in numerical weather prediction (NWP) and weather forecasting. The meeting, spanning 2 days, gathered experts on crowdsourced data from both meteorological institutes and universities from Europe and the United States. Scientific presentations highlighted a vast array of possibilities and progress being made globally. Subjects include data from vehicles, smartphones, and private weather stations. Two groups were created to discuss open questions regarding the collection and use of crowdsourced data from different observing platforms. Common challenges were identified and potential solutions were discussed. While most of the work presented was preliminary, the results shared suggested that crowdsourced observations have the potential to enhance NWP. A common platform for sharing expertise, data, and results would help crowdsourced data realise this potential.
Greening the Survivable Optical Networks: Solutions and Challenges for the Backbone and Access

Electricity consumption contributes to a considerably large amount of the Greenhouse Gas (GHG) emissions while Information and Communication Technologies (ICT) have a significant impact on the electricity usage. Hence, novel network and component architectures leading to energy savings as well as energy-efficient network protocols have emerged since mid-2000s. On the other hand, telecommunication networks are being designed and managed to meet the bandwidth and quality of service requirements of the Internet users. As the bandwidth requests increase tremendously, service availability emerges as a key provisioning metric, since huge data losses may occur even if the service unavailability due to a network failure lasts a short time. Survivable network design and management increases resourceoverbuild due to the deployment of spare resources. Obviously, deployment of spare resources increases energy consumption while establishing robust connections. Thus, “green survivability” arises as a new paradigm constrained to the trade-off between energy consumption of the network equipments versus high reliability for the subscribers. This chapter points out the challenges and explains the recent trends in provisioning green survivability for the optical backbone and access networks. DOI: 10.4018/978-1-4666-1842-8.ch012
Effect of a Magnetic Filter Across the Exit Hole of a Flat Oxygen Plasma Source

This study aims to develop a novel flat oxygen plasma source containing a magnetic filter. The aspect ratio of the diameter to the length of the source vessel was approximately four. A pair of small permanent magnets was inserted in a metal flange to generate the magnetic filter at the exit hole of the plasma source. Measured currentvoltage characteristics indicated that a clear decrease in the electron temperature was successfully attained across the magnetic filter, which was adequate for producing negative oxygen ions via dissociative electron attachment.
The Bethe Equation at q=0, The M"obius Inversion Formula, and Weight Multiplicities: III. The X^{(r)}_N case

It is shown that the numbers of off-diagonal solutions to the U_q(X^{(r)}_N) Bethe equation at q=0 coincide with the coefficients in the recently introduced canonical power series solution of the Q-system. Conjecturally the canonical solutions are characters of the KR (Kirillov-Reshetikhin) modules. This implies that the numbers of off-diagonal solutions agree with the weight multiplicities, which is interpreted as a formal completeness of the U_q(X^{(r)}_N) Bethe ansatz at q=0.
The 13Carbon footprint of B[e] supergiants

We report on the first detection of 13C enhancement in two B[e] supergiants (B[e]SGs) in the Large Magellanic Cloud. Stellar evolution models predict the surface abundance in 13C to strongly increase during main-sequence and post-main-sequence evolution of massive stars. However, direct identification of chemically processed material on the surface of B[e]SGs is hampered by their dense, disc-forming winds, hiding the stars. Recent theoretical computations predict the detectability of enhanced 13C via the molecular emission in 13CO arising in the circumstellar discs of B[e]SGs. To test this potential method and to unambiguously identify a post-main-sequence B[e] SG by its 13CO emission, we have obtained high-quality K-band spectra of two known B[e] SGs in the Large Magellanic Cloud, using the Very Large Telescope's Spectrograph for INtegral Field Observation in the Near-Infrared (VLT/SINFONI). Both stars clearly show the 13CO band emission, whose strength implies a strong enhancement of 13C, in agreement with theoretical predictions. This first ever direct confirmation of the evolved nature of B[e]SGs thus paves the way to the first identification of a Galactic B[e]SG.
Knot probabilities in random diagrams

We consider a natural model of random knotting—choose a knot diagram at random from the finite set of diagrams with n crossings. We tabulate diagrams with 10 and fewer crossings and classify the diagrams by knot type, allowing us to compute exact probabilities for knots in this model. As expected, most diagrams with 10 and fewer crossings are unknots (about 78% of the roughly 1.6 billion 10 crossing diagrams). For these crossing numbers, the unknot fraction is mostly explained by the prevalence of ‘tree-like’ diagrams which are unknots for any assignment of over/under information at crossings. The data shows a roughly linear relationship between the log of knot type probability and the log of the frequency rank of the knot type, analogous to Zipf’s law for word frequency. The complete tabulation and all knot frequencies are included as supplementary data.
COSMIC RAY ACCELERATORS IN THE LARGE MAGELLANIC CLOUD

I point out a correlation between the ∼100 MeV–10 GeV gamma-ray emissivity and the historical star formation rate (SFR) in the Large Magellanic Cloud (LMC) ∼12.5 Myr ago. This correlation bolsters the view that cosmic rays (CRs) in the LMC may be accelerated by conglomerations of supernova remnants (i.e., superbubbles), although it cannot yet be ruled out that other objects—also residing in such high SFR regions—may be responsible for accelerating the particles: indeed, most energetic objects capable of accelerating CRs are expected to reside in high SFR regions.
Mean and variance of absorption time in a population genetics model: Comparison between Markov chain and diffusion process methods.

Finding the expected number of generations it takes before every individual in a population (of constant size) only has one type of gene at a particular locus of a chromosome, can be formulated as computing the mean absorption time in a Markov chain. However, the Markov chain approach is inappropriate when the population is large. This is commonly solved by approximating the Markov chain with a diffusion process, in which the mean absorption time is found by solving an ODE with boundary conditions. In this thesis, the formulas for the mean absorption time is derived in both cases. Using these formulas, the expected number of generations is computed numerically. The two different methods are compared, and we also discuss the genetic meaning of the results. (Less)
Dynsimpie: A Command to Examine Dynamic Compositional Dependent Variables

In this article, we adapt the modeling strategy proposed by Philips, Rutherford, and Whitten (2016, American Journal of Political Science 60: 268–283) and create a user-friendly Stata command, dynsimpie. This command requires the installation of the clarify package of Tomz, Wittenberg, and King (2003, Journal of Statistical Software 8(1): 1–30) and uses the commands in the clarify package to produce estimates from models of compositional dependent variables over time. Users can also examine how counterfactual shocks play through the system with graphs that are easy to interpret. We illustrate this with a model of voter support for the three dominant political parties in the UK.
Designing with the mind in mind : simple guide to understanding user interface design guidelines

In this completely updated and revised edition of Designing with the Mind in Mind, Jeff Johnson provides you with just enough background in perceptual and cognitive psychology that user interface (UI) design guidelines make intuitive sense rather than being just a list or rules to follow. Early UI practitioners were trained in cognitive psychology, and developed UI design rules based on it. But as the field has evolved since the first edition of this book, designers enter the field from many disciplines. Practitioners today have enough experience in UI design that they have been exposed to design rules, but it is essential that they understand the psychology behind the rules in order to effectively apply them. In this new edition, you'll find new chapters on human choice and decision making, hand-eye coordination and attention, as well as new examples, figures, and explanations throughout. It provides an essential source for user interface design rules and how, when, and why to apply them. It arms designers with the science behind each design rule, allowing them to make informed decisions in projects, and to explain those decisions to others. It equips readers with the knowledge to make educated tradeoffs between competing rules, project deadlines, and budget pressures. It completely updated and revised, including additional coverage on human choice and decision making, hand-eye coordination and attention, and new mobile and touch-screen examples throughout.
A New Look at the Daily Cycle of Trade Wind Cumuli

A description of the daily cycle of oceanic shallow cumulus for undisturbed boreal winter conditions in the North Atlantic trades is presented. Modern investigation tools are used, including storm‐resolving and large‐eddy simulations, run over large domains in realistic configurations, and observations from in situ measurements and satellite‐based retrievals. Models and observations clearly show pronounced diurnal variations in cloudiness, both near cloud base and below the trade inversion. The daily cycle reflects the evolution of two cloud populations: (i) a population of nonprecipitating small cumuli with weak vertical extent, which grows during the day and maximizes around sunset, and (ii) a population of deeper precipitating clouds with a stratiform cloud layer below the trade inversion, which grows during the night and maximizes just before sunrise. Previous studies have reported that cloudiness near cloud base undergoes weak variations on time scales longer than a day. However, here we find that it can vary strongly at the diurnal time scale. This daily cycle could serve as a critical test of the models' representation of the physical processes controlling cloudiness near cloud base, which is thought to be key for the determination of the Earth's climate response to warming.
The construction of geological database with Map GIS and Oracle

与普通的数据相比,地质数据有着多源、多量、多类、多元、多维、多主题等特点. 由于地质数据自身的特点,如何有效地存储管理海量地质成果资料和相关信息要素,已经成为当前的热门研究课题. 以矿产资源潜力评价数据为例,在Oracle 10G、MapGIS K9平台基础上完成全国矿产资源潜力评价数据的数据库建设工作. 在原有软件的基础上,对海量地质数据进行统一管理,为地质数据的应用提供基础保障,从而提高地质数据的信息化服务能力.
A Privacy Preservation Method for High Dimensional Data Mining

This paper proposes a privacy preservation method based on random projection to overcome the curse of dimensionality in privacy preserving data mining.To prevent leaks of random matrix which can lead to the reconstruction attack,it first proposes the concepts of secure subspace and secure subspace mapping.Then,it constructs a secure subspace mapping using hash technique,which is implemented by arandom projection matrix,and it achieves a low distortion embedding while preserving the data privacy.Finally,it proves that the secure subspace can preserve the Euclidean distance and inner product between any two original points.The experimental results show that the proposed technique can ensure the data quality in different datamining applications effectively under the precondition of preserving data privacy.