Miracle-dz/UniFAR-FTUs huggingface dataset:
A DESIGN OF POWER AND AREA EFFICIENT FIR FILTER USING APPROXIMATE MULTIPLIERS

— In this paper, In Digital Signal Processing, Finite Impulse Response (FIR) filter is mostly used for communications and radar applications. The Performance of FIR filter depends on Multiplier and adder circuits used in filter. The key blocks of the filter are multipliers and adders, in which multiplier is the one which occupies the major silicon area and consumes more Area, Delay and Power. In this paper, we present a novel approximate computing scheme suitable for realizing the energy-efficient multiply-accumulate (MAC) processing. First we design the approximate 4-2 compressors generating errors in the opposite direction while minimizing the computational costs. Based on the probabilistic analysis, positive and negative multipliers are then carefully developed to provide a similar error distance. Simulation results on various practical applications reveal that the proposed MAC processing offers the energy-efficient computing scenario by extending the range of approximate parts. The proposed FIR filter architecture with length of 6-tap are developed using Verilog HDL and Simulated by Modelsim 6.4c and Synthesized by Xilinx Tool. The Proposed Design is implemented using Spartan 3 XC 3S 200 PQ 208 Device.
Privacy, regulations and the value of personal data

: Personal data have an important place in the strategic positioning of Internet firms so as to better target consumers. When these data are combined with other data (from public administrations, for example), processing them can be a matchless source of added value for firms. The new strategies for extracting value from personal data warrant the adoption of appropriate regulations for this market. After identifying the sources of value related to the processing of personal data, this article draws on the academic literature in economics and marketing to shed light both on the strategies eventually adopted by firms for endowing personal data with an economic value and on the new business models that result. Questions are asked about how regulations will protect the privacy of individuals while letting untouched the ability of firms to innovate. Increasing digitization of the economy has augmented the economic functions of personal data, since enormous quantities of data can now be collected, stocked and processed at ever lower costs. 1 Processing personal data enables firms to make better offers to users by reducing the costs of searches, but it can also be at the origin of prejudicial acts of discrimination or of unwanted, inappropriate advertisements directed at these same users (ACQUISTI et al. 2016). This secondary use of personal data can occur without users being aware of it. From an economic viewpoint, this processing of personal data is linked to the fact that this information is a nonrivalrous and nonexcluable good (CECERE et al. 2017).
MIOSPORE ASSEMBLAGE OF THE GANJRA NALLA BEDS, SOUTH REWA GONDvVANA BASIN, VVITH SOME REMARKS ON THE AGE OF THE BEDS

A miopore assembleage containing 23 genera and 42 species from the Ganjra Nalla Beds of the J ohilla Coalfield, Madhya Pradesh is described. The genera Rugasacciles, Pachysaccus, Gondwano pol/is and Rimospora are newly instituted. The stratigraphical position of the Ganjra Nalla Beds is briefly discussed in the light of the plant micro and macrofossil evidences.
Speech Emotion Recognition via Generation using an Attention-based Variational Recurrent Neural Network

The last decade has seen an exponential rise in the number of attention-based models for speech emotion recognition (SER). Most of these models use a spectrogram as the input speech representation and the CNN or RNN or convolutional RNN as the key machine learning (ML) component, and learn feature weights to implement attention. We propose an attention-based model for SER that uses MFCC as the input speech representation and a variational RNN (VRNN) as the key ML component. Since the MFCC is of lower dimension than a spectrogram, the model is size-and data-efﬁcient. The VRNN has been used for problems in vision but rarely for SER. Our model is predictive in nature. At each instant, it infers the emotion class and generates the next observation, computes the generation error, and selectively samples (attends to) the locations of high error. Thus, attention emerges in our model, and does not require learning feature weights. This simple model provides interesting insights when evaluated for SER on benchmark datasets. The model can operate on variable length and inﬁnite duration audio ﬁles. This work is the ﬁrst to explore simultaneous generation and recognition for SER, where the generation capability is necessary for efﬁcient recognition.
SF-DST: Few-Shot Self-Feeding Reading Comprehension Dialogue State Tracking with Auxiliary Task

Few-shot dialogue state tracking (DST) model tracks user requests in dialogue with reliable accuracy even with a small amount of data. In this paper, we introduce an ontology-free few-shot DST with self-feeding belief state input. The self-feeding belief state input increases the accuracy in multi-turn dialogue by summarizing previous dialogue. Also, we newly developed a slot-gate auxiliary task. This new auxiliary task helps classify whether a slot is mentioned in the dialogue. Our model achieved the best score in a few-shot setting for four domains on multiWOZ 2.0.
Large-scale physical model tests on sand-filled geotextile tubes and containers under wave attack

Geotextile encapsulated sand elements, such as geotextile tubes or geotextile containers, are considered more and more as an alternative material for coastal protection. Uncertainty with respect to the stability of geotextile elements under wave attack is one of the reasons why these systems are not applied widely yet. Therefore, large-scale physical model tests focusing on the stability of geotextile containers and tubes under wave attack have been performed in the Delta Flume of Deltares. The first part focuses at the stability of geotextile containers under wave attack; the second part describes the stability of geotextile tubes under wave attack. For the geotextile containers, observed failure mechanisms are described and analysed qualitatively. For the geotextile tubes, a physical sound formula based on a theoretical approach and verified with large-scale physical model tests is suggested for both stability and deformation (settlement) under wave attack. It was concluded that Froude scaling is not suitable for geotextile containers (due to sand migration within the containers) but can be applied for tubes with a relatively high filling degree.
Comparing Balance Abilities in Different Sports

It is known that balance ability has an importance in terms of sportive performance. Balance ability also showed an important relationship between insufficiencies and performance and sports injuries. Object: The aim of this study is to examine balance ability in several sports. Materials and Methods: Totally 48 male and female athletes consisting of Wrestling (W, n: 13), Futsal (F, n: 10), Taekwondo (T, n: 15), and Cross Country Skiing (CCS, n: 10) whose mean ages were 20.2 ± 0.57, 24.4 ± 1.54, 20.4 ± 0.49 and 16.9 ± 0.09respectively, participated voluntarily to this study. Participants' height (cm) was measured with a stadiometer, body weight (kg) was measured with TANITA BC-418 and leg lengthswere measured with a measuring tape. Y-Balance test (cm) was used in the application of balance tests. Findings: The data were statistically evaluated in the SPSS 23 program and the Kruskal Wallis test was applied to determine the relationship between the groups. Tukey test was applied to determine which group caused the difference and the level of significance was chosen as 0.05. In the evaluation, statistically significant difference in the balance parameters was found between Right anterior and WT, FT, F-CCS, T-CCS sports branches, between Right medial and W-F, F-T, F-CCS sports branches, between Left anterior and W-T, W-CCS, F-T, F - CCS, T-CCS sports branches and between Left medial and W-F, F-T, F-CCS sports branches (p0.05). Result: The balance parameter differs according to sports branches. When these differences are evaluated, it can be said that the best results for all balance parameters are for Cross Country Skiing, Taekwondo, Wrestling and Futsal athletes, respectively.
“Before Dawn,” Listening to the Voices of Social Media: A Study on the Public's Response to the COVID-19 Vaccine

The COVID-19 pandemic is a worldwide catastrophe. In the absence of an effective drug, one effective measure to pull the pandemic to the end is herd immunity by taking vaccines, while the hesitation and anti-attitude from social media affect the vaccination. This makes it crucial to evaluate the text data about the COVID-19 vaccine from tweets. The period for data used in this study is 1 Aug to 31 Oct, 2020, since it is just before promoting the use when public reactions to the COVID-19 vaccine can influence their subsequent vaccination behavior. In this study, we used the latent Dirichlet allocation (LDA) topic model and sentiment analysis to explore public reactions to the COVID-19 vaccine. The results indicate that the public discussion could be divided into 11 topics, which could be further summarized into four different themes: (1) concerns about COVID-19; (2) concerns about vaccine development, production, and distribution; (3) how to control the COVID-19 before obtaining the vaccine; and (4) concerns about information of vaccine safety and efficacy. It can be concluded that to a large extent, public reactions to vaccines are dominated by positive sentiment. Specifically, the politicization of the vaccine approval process, suspension of vaccine trials, and measures to control COVID-19 tend to trigger negative public sentiment; whereas information related to successful vaccine development and availability enhances positive public sentiment. These findings help us understand public reactions to the COVID-19 vaccine, uncover potential factors that may influence vaccination behavior, and help policymakers understand public opinion about the COVID-19 vaccine and develop rational and effective policies.
E pur si muove

The averaged term of squared vorticity is attributed to accelerated expansion. Cosmological singularity has been a consequence of excessive symmetry of flow, such as "Hubble's law". More realistic one is suggested. Exact dynamic and steady/static solutions are presented. A "negative radiation" equation of state is generated by vorticity which is the dynamic carrier of the dark energy. This fact dismisses the need in cosmological term, in any modifications of the gravity theory or in an exotic matter. A new concept of a material point is established. The paper comments as well on social and educational aspects of the findings.
Estimating Structurally Similar Graphical Models

This paper considers the problem of estimating the structure of structurally similar graphical models in high dimensions. This problem is pertinent in multi-modal or multi-domain datasets that consist of multiple information domains, each modeled by one probabilistic graphical model (PGM), e.g., in brain network modeling using different neuroimaging modalities. Induced by an underlying shared causal source, the domains, and subsequently their associated PGMs, can have structural similarities. This paper focuses on Gaussian and Ising models and characterizes the information-theoretic sample complexity of estimating the structures of a pair of PGMs in the degree-bounded and edge-bounded subclasses. The PGMs are assumed to have <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> nodes with distinct and unknown structures. Their similarity is accounted for by assuming that a pre-specified set of <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> nodes form identical subgraphs in both PGMs. Necessary and sufficient conditions on the sample complexity for a bounded probability of error are characterized. The necessary conditions are information-theoretic (algorithm-independent), delineating the statistical difficulty of the problem. The sufficient conditions are based on deploying maximum likelihood decoders. While the specifics of the results vary across different subclasses and parameter regimes, one key observation is that in specific subclasses and regimes, the sample complexity varies with <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> according to <inline-formula> <tex-math notation="LaTeX">$\Theta (\log (p-q))$ </tex-math></inline-formula>. For Ising models, a low complexity, online structure estimation (learning) algorithm based on multiplicative weights is also proposed. Numerical evaluations are also included to illustrate the interplay among different parameters on the sample complexity when the structurally similar graphs are recovered by a maximum likelihood-based graph decoder and the proposed online estimation algorithm.
Significance of single frequency filter for the development of children's KWS system

Spotting a deﬁned set of keywords from a running speech is known as keyword spotting (KWS). When keywords are detected using speech data from child speakers with the acoustic model built using speech data from adult speakers, it is named as childrens KWS system. Owing to the differences in pitch and speaking rate between the two kind of speakers, the performance of childrens KWS system deteriorates severely. In this paper, a pitch independent feature extraction method is proposed exploiting single frequency ﬁltering (SFF) approach to address this issue. The method aims at ﬁnding the amplitude envelopes at Mel spaced frequencies. These amplitude envelopes are then averaged per analysis frame. Logarithm of the means are computed followed by Discrete Cosine Transform (DCT) to determine the required pitch robust feature, here denoted as Mel spaced single frequency ﬁltering cepstral coefﬁcient (MS-SFF-CC). The proposed feature outperforms several explored features with acoustic model trained on deep neural network-hidden Markov model (DNN-HMM) under pitch matched and mismatched test scenarios without and with data-augmented training.
Evaluating the Effects of Riparian Habitat Type on Nutrient Concentrations in Agricultural Headwater Streams

Grass filter strips and other riparian buffer types are frequently used in agricultural watersheds to reduce nonpoint source pollution, but there is only limited information available on their long‐term watershed scale effects. Our research questions were as follows: (1) does nutrient concentrations differ among agricultural headwater streams with different riparian habitat types? and (2) does the effect of riparian habitat type differ annually or seasonally? Eight streams in central Ohio were selected based on watershed size, proportion of watershed agricultural land use, and riparian habitat type. Three streams possessed unplanted riparian habitats, three streams had grass filter strips, and two streams had forested riparian habitats. Water samples for the measurement of ammonia, nitrate + nitrite, total nitrogen, dissolved reactive phosphorus, total phosphorus, and dissolved organic carbon concentrations were collected weekly from two sites in each stream from March 2007 to February 2017. Mean nitrogen and phosphorus concentrations did not differ (p > 0.05) among riparian habitat types. Mean dissolved organic carbon concentrations exhibited different (p < 0.05) annual and seasonal trends among riparian habitat types. Our results indicated that planting grass filter strips alone may not decrease nitrogen and phosphorus concentrations and highlighted the influence of riparian woody vegetation on the temporal dynamics of dissolved organic carbon concentrations.
A Quantitative Analysis of the Source of Inter‐Model Spread in Arctic Surface Warming Response to Increased CO2 Concentration

This study exams the main sources of inter‐model spread in Arctic amplification of surface warming simulated in the abrupt‐4 × CO2 experiments of 18 CMIP6 models. It is found that the same seasonal energy transfer mechanism, namely that the part of extra solar energy absorbed by Arctic Ocean in summer due to sea‐ice melting is temporally stored in ocean in summer and is released in cold months, is responsible for the Arctic amplification in each of the 18 simulations. The models with more (less) ice melting and heat storing in the ocean in summer have the stronger (weaker) ocean heat release in cold season. Associated with more (less) heat release in cold months are more (less) clouds, stronger (weaker) poleward heat transport, and stronger (weaker) upward surface sensible and latent heat fluxes. This explains why the Arctic surface warming is strongest in the cold months and so is its inter‐model spread.
The properties of outbursts and long-term activity of the soft X-ray transient 4U 1608-52 (QX Nor)

An analysis of the long-term activity of 4U 1608–52, based on the $ASM/RXTE$ data, is presented. Although the individual outbursts in 4U 1608–52 differ in both their duration and peak intensity, their rising and final decay branches display remarkable similarities. The variations of the soft X-ray color between 1.5–4 keV are found to follow the luminosity during the decay of outburst much better than the variations between 4–12 keV. The recurrence time T C of outbursts was analyzed by the method of the $\rm O{-}C$ residuals. The mean value of T C is 330 days between the years 1996–2003 but a strong long-term trend of a decreasing T C can be resolved. A series of four or five consecutive outbursts displays a clear correlation between the decreasing T C and increasing peak intensity, but no correlation with the outburst duration. The observed behaviour is discussed in terms of the thermal instability model. We argue that the disk viscosity achieves similar values for the individual outbursts in 4U 1608–52. Only during the brightest outbursts does the luminosity appear to be high enough for the disk to be ionized out to its outer rim by the X-rays from the neutron star, according to the model by King & Ritter ([CITE]). We also argue that the disk is never considerably depleted in outburst. A comparison with the similar system, Aql X-1, helps us to find the common links between the disk behaviour in the individual neutron-star soft X-ray transients.
HOST GALAXY PROPERTIES OF THE SWIFT BAT ULTRA HARD X-RAY SELECTED ACTIVE GALACTIC NUCLEUS

We have assembled the largest sample of ultra hard X-ray selected (14–195 keV) active galactic nucleus (AGN) with host galaxy optical data to date, with 185 nearby (z < 0.05), moderate luminosity AGNs from the Swift BAT sample. The BAT AGN host galaxies have intermediate optical colors (u − r and g − r) that are bluer than a comparison sample of inactive galaxies and optically selected AGNs from the Sloan Digital Sky Survey (SDSS) which are chosen to have the same stellar mass. Based on morphological classifications from the RC3 and the Galaxy Zoo, the bluer colors of BAT AGNs are mainly due to a higher fraction of mergers and massive spirals than in the comparison samples. BAT AGNs in massive galaxies (log M* >10.5) have a 5–10 times higher rate of spiral morphologies than in SDSS AGNs or inactive galaxies. We also see enhanced far-infrared emission in BAT AGN suggestive of higher levels of star formation compared to the comparison samples. BAT AGNs are preferentially found in the most massive host galaxies with high concentration indexes indicative of large bulge-to-disk ratios and large supermassive black holes. The narrow-line (NL) BAT AGNs have similar intrinsic luminosities as the SDSS NL Seyferts based on measurements of [O iii] λ5007. There is also a correlation between the stellar mass and X-ray emission. The BAT AGNs in mergers have bluer colors and greater ultra hard X-ray emission compared to the BAT sample as a whole. In agreement with the unified model of AGNs, and the relatively unbiased nature of the BAT sources, the host galaxy colors and morphologies are independent of measures of obscuration such as X-ray column density or Seyfert type. The high fraction of massive spiral galaxies and galaxy mergers in BAT AGNs suggest that host galaxy morphology is related to the activation and fueling of local AGN.
One-step models in pitch perception: Experimental evidence from Japanese

Several psycholinguistic and computational models have examined the perception of illusory vowels , where listeners of a language insert an epenthetic vowel to repair illegal consonant clusters, perceiving VCCV as VCVCV. This study investigated whether these top-down effects can be extended to pitch patterns and induce illusory pitches , where a pitch was perceived on the epenthetic vowel. Tokyo and Kinki Japanese are two dialects in Japan with the same phonotactics, but Tokyo and Kinki Japanese regard LLH (low low high) and LHH as illegal tonal patterns, respectively. We used an index representing linguistic exposure to the Tokyo pitch pattern and had an AXB discrimination task to investigate whether the pitch patterns inﬂuence the perception. We found that Tokyo dialect listeners with the high index, who have long exposure to the Tokyo pitch pattern, perceived “H” pitch between L and H, whereas the subjects with the low index did not show any preference. These results in-dicated that pitch patterns were also used in the perception of illusory pitches and were reproduced in a simulation study.
Construction and validation of a corruption perception scale at the citizen level

Abstract The study described the creation and validation of the Corruption Perception Scale (CPS), which assesses how citizens perceive corruption. In a qualitative step, the instrument was evaluated by experts, followed by a pre-test. In the quantitative step, exploratory and confirmatory factor analysis was performed, totaling a sample of 1,075 cases. Finally, a methodology for the application of CPS was suggested. The final structure of the measure was composed of five dimensions at the individual level (knowledge, behavior, reflexes, control, and attitude), which position the citizen as the protagonist in the analysis of the phenomenon.
Lévy Processes and Stochastic Calculus: Lévy processes

Levy processes form a wide and rich class of random process, and have many applications ranging from physics to finance. Stochastic calculus is the mathematics of systems interacting with random noise. Here, the author ties these two subjects together, beginning with an introduction to the general theory of Levy processes, then leading on to develop the stochastic calculus for Levy processes in a direct and accessible way. This fully revised edition now features a number of new topics. These include: regular variation and subexponential distributions; necessary and sufficient conditions for Levy processes to have finite moments; characterisation of Levy processes with finite variation; Kunita's estimates for moments of Levy type stochastic integrals; new proofs of Ito representation and martingale representation theorems for general Levy processes; multiple Wiener-Levy integrals and chaos decomposition; an introduction to Malliavin calculus; an introduction to stability theory for Levy-driven SDEs.