Miracle-dz/UniFAR-FTUs huggingface dataset:
Invariants of gradient (Morse) complexes and artificial neural nets

There is canonical partition of set of critical values of function into pairs "birth-death" and a separate set representing basis in Betti homology, as was established in S.Barannikov "The Framed Morse complex and its invariants" Adv. in Sov. Math., vol 21, AMS transl, (1994). This partition arises from bringing the gradient (Morse) complex to so called "canonical form" by a linear transform respecting the filtration defined by the order of the critical values. These "canonical forms" are combinatorial invariants of R-filtered complexes. Starting from the beginning of 2000s these invariants became widely used in applied mathematics under the name of "Persistence diagrams" and "Persistence Bar-codes". The canonical form of an R-filtered complex is the partition of the set of critical values (indices of filtration) into "birth-death" pairs and a separate set representing homology of the complex. The "canonical form" invariants are obtained by action of upper-triangular matrices, which reduces the R-filtered complex to the simplest form. In this note I give a short introduction into the subject of these invariants. I also propose application of these invariants to artificial neural nets.
Evaluation of Rainfall Forecasts with Heavy Rain Types in the High-Resolution Unified Model over South Korea

Heavy rainfall events account for most socioeconomic damages caused by natural disasters in South Korea. However, the microphysical understanding of heavy rain is still lacking, leading to uncertainties in quantitative rainfall prediction. This study is aimed at evaluating rainfall forecasts in the Local Data Assimilation and Prediction System (LDAPS), a high-resolution configuration of the Unified Model over the Korean Peninsula. The rainfall of LDAPS forecasts was evaluated with observations based on two types of heavy rain events classified from K-means clustering for the relationship between surface rainfall intensity and cloud-top height. LDAPS forecasts were characterized by more heavy rain cases with high cloud-top heights (cold-type heavy rain) in contrast to observations showing frequent moderate-intensity rain systems with relatively lower cloud-top heights (warm-type heavy rain) over South Korea. The observed cold-type and warm-type events accounted for 32.7% and 67.3% of total rainfall, whereas LDAPS forecasts accounted for 65.3% and 34.7%, respectively. This indicates severe overestimation and underestimation of total rainfall for the cold-type and warm-type forecast events, respectively. The overestimation of cold-type heavy rainfall was mainly due to its frequent occurrence, whereas the underestimation of warm-type heavy rainfall was affected by both its low occurrence and weak intensity. The rainfall forecast skill for the warm-type events was much lower than for the cold-type events, due to the lower rainfall intensity and smaller rain area of the warm-type. Therefore, cloud parameterizations for warm-type heavy rain should be improved to enhance rainfall forecasts over the Korean Peninsula.
Nonlinear modeling of the effect of n  =  2 resonant magnetic field perturbation on peeling-ballooning modes in KSTAR

Using the nonlinear 3D MHD code JOREK with reduced MHD equations (visco-resistive MHD), we have successfully simulated a recent n = 2 resonant magnetic perturbation (RMP)-driven edge localized mode (ELM) suppression in KSTAR. We have found that such ELM suppression has been attributable not only to the degraded pedestal but also to the direct coupling between the peeling-ballooning mode (PBM) and RMP-driven plasma response. Notably, the pedestal pressure gradient is reduced as the radial transport is enhanced because of the formation of the stochastic layer and increased convection fluxes due to tearing and the kink-peeling mode driven by RMPs. The increased transport in the stochastic layer is due to the parallel transport across the stochastic fields, described by the Braginskii model in the simulation. While the linear stability of the PBM improves owing to the degraded pedestal, it is not a sole contributor to ELM suppression, in that the nonlinear mode coupling plays a more critical role. This outcome is consistent with previous studies where mode coupling affects the ELM mitigation or suppression. In addition, PBM locking has been numerically achieved during the ELM suppression phase, which may support the relationship between at the pedestal and the onset of ELM suppression. We suggest that PBM locking can enhance the mode interactions between RMPs and PBMs, which is significant for ELM suppression.
Understanding Galaxy Evolution Through Emission Lines

We review the use of emission lines for understanding galaxy evolution, focusing on excitation source, metallicity, ionization parameter, ISM pressure, and electron density. We discuss the physics, benefits, and caveats of emission line diagnostics, including the effects of theoretical model uncertainties, diffuse ionized gas, and sample selection bias. In anticipation of upcoming telescope facilities, we provide new self-consistent emission line diagnostic calibrations for complete spectral coverage from the UV to the IR. These diagnostics can be used in concert to understand how fundamental galaxy properties have changed across cosmic time. We conclude the following: ▪ The UV, optical, and IR contain complementary diagnostics that can probe the conditions within different nebular ionization zones. ▪ Accounting for complex density gradients and temperature profiles is critical for reliably estimating the fundamental properties of Hii regions and galaxies. ▪ Diffuse ionized gas can raise metallicity estimates, flatten metallicity gradients, and introduce scatter in ionization parameter measurements. ▪ New 3D emission line diagnostics successfully separate the contributions from star formation, AGN, and shocks using integral field spectroscopy. We summarize with a discussion of the challenges and major opportunities for emission line diagnostics in the coming years.
Blow up and globality of solutions for a nonautonomous semilinear heat equation with Dirichlet condition

In this paper we prove the local existence of a nonnegative mild solution for a nonautonomous semilinear heat equation with Dirichlet condition, and give sucient conditions for the globality and for the blow up infinite time of the mild solution. Our approach for the global existence goes back to the Weissler's technique and for the nite time blow up we uses the intrinsic ultracontractivity property of the semigroup generated by the diffusion operator.
Countermeasures for advanced unambiguous state discrimination attack on quantum key distribution protocol based on weak coherent states

In this paper we investigate the advanced unambiguous state discrimination (USD) attack that is crucial for quantum key distribution based on phase-coded coherent states. Performing the attack Eve imposes all discriminated states while she can maintain both detection and error rates at Bob’s side. In this work we give the detailed description of the attack and propose the general approach for countermeasures. As the particular case we introduce the so-called ‘mousetrap’ (uninformative) state which allows to decrease the USD probability and preserve high sifted key rate. We also propose some candidates for ‘mousetrap’ states and provide the estimation on the discrimination probability for each of them.
Palm Kernel Oil as a Substitute of Milk Fat in Feta Cheese

Four samples of Feta cheese 5 Kg/each made by substituting buffalo milk fat with palm kernel oil (PKO). The substituting ratios were 25%, 50%, 75% and 100% (PKO) to milk fat (MF). Fat content of the obtained cheese was 40% fat/dry matter. A control batch contained milk fat with the same fat content was prepared. The resultant cheese samples were stored at room temperature for three months. Samples were analyzed monthly during pickling period to investigate the effect of the treatment with (PKO) on cheese yield, gross composition, organoleptic properties and the changes in fatty acids pattern of fat content of the resultant cheese samples. The results showed that substituting of milk fat with different ratios of (PKO) caused a significant increase in moisture content, when compared with the control, while the total solids decreased. Cheese yield of all cheese treatments decreased as pickling period progressed. Moisture content of the cheese decreased, whereas fat, total protein and ash contents increased as pickling period progressed. Cheese flavor was enhanced in cheese containing different ratios of (PKO), while the texture of cheese widely depended on the ratio of (PKO) added. Cheese samples showed a similar color and appearance to the control.The changed occurred in fatty acids pattern of the examined samples showed that the addition of (PKO) as a milk fat substitute at ratios 25%, 50%, 75% and 100%, resulted in an increase in the total medium chain fatty acids of the cheese fat when compared with milk fat. Cheese samples treated with 25% and 50% (PKO) were of the higher score of the acceptability due to the presence of medium chain fatty acids. It could be concluded that the use of (PKO) as buffalo's milk fat substitute succeeded in making Feta cheese of healthy and of acceptance for the consumers.
Aplikasi Tuner Alat Musik Sasando Real-Time Menggunakan Teknik Fast Fourier Transform (FFT) dan Harmonic Product Spectrum (HPS)

ABSTRAK Tujuan dari penelitian ini adalah untuk mendesain suatu aplikasi tuner sasando yang memiliki tingkat akurasi yang tinggi dalam mendeteksi frekuensi fundamental dari jenis sasando 32 senar menggunakan Algoritma Fast Fourier Transform (FFT) dan Harmonic Product Spectrum (HPS). Tingkat akurasi yang tinggi ditentukan dari resolusi frekuensi yang tinggi. Menurut Lourde, M (2009), kemampuan telinga manusia untuk membedakan bunyi adalah pada resolusi 0.5 Hz. Manusia tidak mampu membedakan bunyi jika resolusi atau selisih dua frekuensi yang berdekatan lebih kecil dari 0.5 Hz. Oleh karena itu, aplikasi yang didesain harus mampu memberikan resolusi 0.5 Hz. Berdasarkan hasil simulasi, Aplikasi Tuner sasando yang telah dibangun mampu memberikan output resolusi 0.5 Hz. Selain itu, aplikasi yang dibangun juga dapat menampilkan spektrum frekuensi dan mampu memberikan informasi apabila frekuensi dari senar yang sedang dituning sudah tepat pada frekuensi fundamentalnya. Tidak hanya itu, apabila frekuensinya masih kurang atau sudah melewati frekuensi dasarnya, maka akan ditampilkan juga pada outputnya.
A Survey of Automatic Parameter Tuning Methods for Metaheuristics

Parameter tuning, that is, to find appropriate parameter settings (or configurations) of algorithms so that their performance is optimized, is an important task in the development and application of metaheuristics. Automating this task, i.e., developing algorithmic procedure to address parameter tuning task, is highly desired and has attracted significant attention from the researchers and practitioners. During last two decades, many automatic parameter tuning approaches have been proposed. This paper presents a comprehensive survey of automatic parameter tuning methods for metaheuristics. A new classification (or taxonomy) of automatic parameter tuning methods is introduced according to the structure of tuning methods. The existing automatic parameter tuning approaches are consequently classified into three categories: 1) simple generate-evaluate methods; 2) iterative generate-evaluate methods; and 3) high-level generate-evaluate methods. Then, these three categories of tuning methods are reviewed in sequence. In addition to the description of each tuning method, its main strengths and weaknesses are discussed, which is helpful for new researchers or practitioners to select appropriate tuning methods to use. Furthermore, some challenges and directions of this field are pointed out for further research.
FAKTOR YANG BERHUBUNGAN DENGAN KEJADIAN DBD DI PULAU BALANG LOMPO KABUPATEN PANGKEP

Penyakit DBD merupakan penyakit menular yang terutama menyerang anak-anak. Penularan penyakit ini disebabkan oleh penyebarannya sangat cepat dan sering menimbulkan wabah yang luar biasa, sehingga menyebabkan banyak kesakitan bahkan sampai pada kematian. Permasalahan ini sering muncul dan berulang bersamaan dengan datangnya musim hujan di Indonesia, dan ditunjang kurangnya kesadaran akan kebersihan lingkungan dari masyarakat setempat. Penelitian ini bertujuan Untuk mengetahui faktor yang berhubungan dengan kejadian DBD Di Pulau Balang Lompo Kabupaten Pangkep. Jenis penelitian ini yaitu jenis penelitian observasional dengan cara pendekatan cross sectional. Populasi adalah seluruh rumah tangga dengan jumlah 300 rumah yang ada di Kelurahan Mattiro Sompe Pulau Balang Lompo Kab. Pangkep. Sampel yang digunakan yaitu sebanyak 171 rumah. Analisa data dengan menggunakan uji satatistik “Chi-Square (X²)” yang diperoleh dari hasil observasi dan wawancara dari jawaban kuesioner kemudian diolah dan disajikan dalam bentuk tabel. Hasil penelitian menunjukkan bahwa ada hubungan antara Kepadatan Jentik dengan Kejadian DBD di Pulau Balang Lompo yaitu hasil uji chi square diperoleh nilai p= 0,018 < α= 0,05, ada hubungan antara Pemberantasan Sarang Nyamuk (PSN) atau gerakan 3M dengan kejadian DBD hasil uji chi square diperoleh nilai p= 0,000 < α= 0,05, ada hubungan antara Mobilitas Penduduk dengan kejadian DBD yaitu hasil uji chi square diperoleh nilai p= 0,000 lebih < α= 0,05 dan tidak ada hubungan antara Kebiasaan Menggantung Pakaian Dalam Rumah dengan kejadian DBD. Hal tersebut didasarkan pada hasil uji chi square diperoleh nilai p= 0,819 > α= 0,05. Kesimpulan dari peneltian ini adalah ada hubungan antara kepadatan jentik Aedes aegypti, ada hubungan antara Pemberantasan Sarang Nyamuk (PSN) salah satunya pelaksanaan 3M,dan ada hubungan antara mobilitas penduduk dengan kejadian DBD. Sedangkan tidak ada hubungan antara kebiasaan menggantung pakaian dalam rumah dengan kejadian DBD di Pulau Balang Lompo Kelurahan Mattiro Sompe Kec. Liukang Tupabbiring Kab. Pangkep.Kata kunci : DBD, Aedes aegypti, 3M
Multipole Analysis of Radio Continuum Images of Supernova Remnants: Comparison of Type Ia and Core Collapse

A multipole expansion analysis is applied to 1420 MHz radio continuum images of supernova remnants (SNRs) in order to compare Type Ia and core collapse (CC) SNRs. Because the radio synchrotron emission is produced at the outer shock between the SNR and the ISM, we are investigating whether the ISM interaction of SNRs is different between Type Ia and CC SNRs. This is in contrast to previous investigations, which have shown that Type Ia and CC SNRs have different asymmetries in the X-ray emission from their ejecta. The sample consists of 19 SNRs which have been classified as either Type Ia or CC. The quadrupole and octupole moments normalized to their monopole moments (total emission) are used as a measure of asymmetry of the emission. A broad range (by a factor of ~1000) is found for both quadrupole and octupole normalized moments. The strongest correlation we find is that large quadrupole moments are associated with large octupole moments, indicating that both serve as similar indicators of asymmetry. The other correlation we find is that both moments increase with SNR age or radius. This indicates that interstellar medium structure is a strong contributor to asymmetries in the radio emission from SNRs. This does not seem to apply to molecular clouds, because we find that association of a SNR with a molecular cloud is not correlated with larger quadrupole or octupole moments.
Asymptotic results for weighted means of linear combinations of independent Poisson random variables

ABSTRACT In this paper we prove the large deviation principle for a class of weighted means of linear combinations of independent Poisson distributed random variables, which converge weakly to a normal distribution. The interest in these linear combinations is motivated by the diffusion approximation in Lansky [On approximations of Stein's neuronal model, J. Theoret. Biol. 107 (1984), pp. 631–647] of the Stein's neuronal model (see Stein [A theoretical analysis of neuronal variability, Biophys. J. 5 (1965), pp. 173–194]). We also prove an analogue result for sequences of multivariate random variables based on the diffusion approximation in Tamborrino, Sacerdote, and Jacobsen [Weak convergence of marked point processes generated by crossings of multivariate jump processes. Applications to neural network modeling, Phys. D 288 (2014), pp. 45–52]. The weighted means studied in this paper generalize the logarithmic means. We also investigate moderate deviations.
Direct numerical simulation of decaying homogeneous isotropic turbulence — numerical experiments on stability, consistency and accuracy of distinct lattice Boltzmann methods

Stability, consistency and accuracy of various lattice Boltzmann schemes are investigated by means of numerical experiments on decaying homogeneous isotropic turbulence (DHIT). Therefore, the Bhatnagar–Gross–Krook (BGK), the entropic lattice Boltzmann (ELB), the two-relaxation-time (TRT), the regularized lattice Boltzann (RLB) and the multiple-relaxation-time (MRT) collision schemes are applied to the three-dimensional Taylor–Green vortex, which represents a benchmark case for DHIT. The obtained turbulent kinetic energy, the energy dissipation rate and the energy spectrum are compared to reference data. Acoustic and diffusive scaling is taken into account to determine the impact of the lattice Mach number. Furthermore, three different Reynolds numbers [Formula: see text], [Formula: see text] and [Formula: see text] are considered. BGK shows instabilities, when the mesh is highly underresolved. The diverging simulations for MRT are ascribed to a strong lattice Mach number dependency. Despite the fact that the ELB modifies the bulk viscosity, it does not mimic a turbulence model. Therefore, no significant increase of stability in comparison to BGK is observed. The TRT “magic parameter” for DHIT at moderate Reynolds numbers is estimated with respect to the energy contribution. Stability and accuracy of the TRT scheme is found to be similar to BGK. For small lattice Mach numbers, the RLB scheme exhibits lowered energy contribution in the dissipation range compared to an analytical model spectrum. Overall, to enhance stability and accuracy, the lattice Mach number should be chosen with respect to the applied collision scheme.
On the meaning of the wave function of the Universe

The meaning of the wave function of the Universe was actively discussed in 1980s. In most works on quantum cosmology, it is accepted that the wave function is a probability amplitude for the Universe to have some space geometry, or to be found in some point of the Wheeler superspace. It seems that the wave function gives maximally objective description compatible with quantum theory. However, the probability distribution does not depend on time and does not take into account the existing of our macroscopic evolving Universe. What we wish to know is how quantum processes in the Early Universe determined the state of the present Universe in which we are able to observe macroscopic consequences of these quantum processes. As an alternative to the Wheeler–DeWitt quantum geometrodynamics, we consider the picture that can be obtained in the extended phase space approach to quantization of gravity. The wave function in this approach describes different states of the Universe which correspond to different stages of its evolution.
Runtime Verification on Hierarchical Properties of ROS-Based Robot Swarms

Various robots are playing critical roles in many areas such as industrial manufacturing, disaster rescuing, unmanned vehicle, and science exploration. Because of the uncertain environment, changed resource, or dynamic system structure at runtime, traditional methods such as testing, model checking, and static analysis used in the development stage are not enough to ensure that the executions of robot control software satisfy specified properties. In this paper, we propose a runtime verification approach called Robots Monitor on Multilayer (RMoM) based on robot operating system (ROS) for monitoring whether the running of a robot swarm violates given temporal properties. To monitor robot system in a comprehensive manner over multiple layers, RMoM unifies resource, communication, robot, and swarm properties into a systemic, hierarchical monitoring framework. A discrete-time Metric Temporal Logic (MTL<inline-formula><tex-math notation="LaTeX">$_3$</tex-math></inline-formula>) RMoM is proposed for specifying properties with timed and parameterized characteristics in robot swarms. Then, the corresponding three-valued semantics is defined for MTL<inline-formula><tex-math notation="LaTeX">$_3$</tex-math></inline-formula>-RMoM to generate impartial and anticipatory monitors. Moreover, a hierarchical monitoring specification language high-level specification language (HSL)-RMoM and a series of monitor construction algorithms are proposed to automatically generate monitors for MTL<inline-formula><tex-math notation="LaTeX">$_3$</tex-math></inline-formula>-RMoM properties on ROS platform. The experiments show that the method can automatically generate the monitors for detecting properties of robot swarms.
Incorporating Prior Information in Nonnegative Matrix Factorization for Audio Source Separation

In this work, we propose solutions to the problem of audio source separation from a single recording. The audio source signals can be speech, music or any other audio signals. We assume training data for the individual source signals that are present in the mixed signal are available. The training data are used to build a representative model for each source. In most cases, these models are sets of basis vectors in magnitude or power spectral domain. The proposed algorithms basically depend on decomposing the spectrogram of the mixed signal with the trained basis models for all observed sources in the mixed signal. Nonnegative matrix factorization (NMF) is used to train the basis models for the source signals. NMF is then used to decompose the mixed signal spectrogram as a weighted linear combination of the trained basis vectors for each observed source in the mixed signal. After decomposing the mixed signal, spectral masks are built and used to reconstruct the source signals. In this thesis, we improve the performance of NMF for source separation by incorporating more constraints and prior information related to the source signals to the NMF decomposition results. The NMF decomposition weights are encouraged to satisfy some prior information that is related to the nature of the source signals. The priors are modeled using Gaussian mixture models or hidden Markov models. These priors basically represent valid weight combination sequences that the basis vectors can receive for a certain type of source signal. The prior models are incorporated with the NMF cost function using either log-likelihood or minimum mean squared error estimation (MMSE). We also incorporate the prior information as a post processing. We incorporate the smoothness prior on the NMF solutions by using post smoothing processing. We also introduce post enhancement using MMSE estimation to obtain better separation for the source signals. In this thesis, we also improve the NMF training for the basis models. In cases when enough training data are not available, we introduce two different adaptation methods for the trained basis to better fit the sources in the mixed signal. We also improve the training procedures for the sources by learning more discriminative dictionaries for the source signals. In addition, to consider a larger context in the models, we concatenate neighboring spectra together and train basis sets from them instead of a single frame which makes it possible to directly model the relation between consequent spectral frames. Experimental results show that the proposed approaches improve the performance of using NMF in source separation applications