Miracle-dz/UniFAR-FTUs huggingface dataset:
Blind Amplitude Estimation of Early Room Reflections Using Alternating Least Squares

Estimation of the properties of early room reflections is an important task in audio signal processing, with applications in beamforming, source separation, room geometry inference, and spatial audio. While methods exist to blindly estimate the direction of arrival and delay of the early reflections, the blind estimation of reflection amplitudes remains an open problem. This work presents a preliminary attempt to blindly estimate reflection amplitudes. An iterative estimator is suggested, based on maximum likelihood and alternating least squares. We discuss some fundamental scaling ambiguities of the problem, and show connections between the proposed method and raking beamformers. A simulation study demonstrates the effectiveness of the proposed method.
Cross-media measurement with Virtual People

We introduce methods for eﬃcient and privacy-safe modeling of reach and the demographic composition of cross-media campaigns. Cross-media campaign traﬃc is composed of two parts: digital and TV. Digital traﬃc is estimated based on event-level data available in server logs. TV traﬃc is extrapolated from a combination of panel and set-top-box or smart-TV data. The Virtual-People methodology introduced in [9] allows for eﬃcient measurement of digital audiences. In this paper we extend this methodology to work with the extrapolated data sources associated with TV data, thus generalizing it for cross-media measurement
Prognostic Significance of Microvascular Invasion in Pancreatic Ductal Adenocarcinoma: A Systematic Review and Meta-Analysis

Background The incidence, pathogenesis, and prognostic effect of microvascular invasion on pancreatic ductal adenocarcinoma (PDAC) remain controversial. This study aimed to summarize the incidence, pathogenesis, role in clinical management, recurrence, and prognostic significance of microvascular invasion in PDAC. Material/Methods A literature review and meta-analysis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Systematic literature searches were conducted using PubMed and Google Scholar up to February 2021. Results Seventeen studies were included in the meta-analysis. The incidence of microvascular invasion was 49.0% (95% confidence interval [CI], 43.8–54.5%) among PDAC patients who underwent surgery. The weighted multivariate Cox proportional hazards model hazard ratio for disease-free survival of 8 studies was 1.78 (95% CI 1.53–2.08, P<0.001), and there was no statistically significant difference between the subgroups (P=0.477). The hazard ratio for overall survival of 14 studies was 1.49 (95% CI 1.27–1.74, P<0.001), and there was no statistically significant difference between the subgroups (P=0.676). Conclusions Microvascular invasion occurred in nearly half of PDAC patients after surgery and was closely related to disease-free and overall survival. Understanding the role of microvascular invasion in PDAC will help provide more personalized and effective preoperative or postoperative strategies to achieve better survival outcomes.
Rearchitecting Linux Storage Stack for µs Latency and High Throughput

This paper demonstrates that it is possible to achieve µ s-scale latency using Linux kernel storage stack, even when tens of latency-sensitive applications compete for host resources with throughput-bound applications that perform read/write operations at throughput close to hardware capacity. Furthermore, such performance can be achieved without any modiﬁcation in applications, network hardware, kernel CPU schedulers and/or kernel network stack. We demonstrate the above using design, implementation and evaluation of blk-switch , a new Linux kernel storage stack architecture. The key insight in blk-switch is that Linux’s multi-queue storage design, along with multi-queue network and storage hardware, makes the storage stack conceptually similar to a network switch. blk-switch uses this insight to adapt techniques from the computer networking literature ( e.g. , multiple egress queues, prioritized processing of individual requests, load balancing, and switch scheduling) to the Linux kernel storage stack. blk-switch evaluation over a variety of scenarios shows that it consistently achieves µ s-scale average and tail latency (at both 99 th and 99 . 9 th percentiles), while allowing applications to near-perfectly utilize the hardware capacity.
An Overview of Image Steganographic Techniques

: Steganography is the art of hiding information in ways that prevent the detection of hidden messages. Steganography, derived from Greek, literally means "Covered writing". It includes a vast array of secret communication methods that conceal the message's very existence. These methods include invisible inks, microdots, character arrangement, digital signatures, covert channels, and spread spectrum communications. Steganographic applications only require the flexibility to alter cover object in order to be able to embed the hidden information. For this reason any type of digital object can be potentially used as a cover object. For example, images, audio, streaming data, software or natural language text have been used as cover objects. The secrecy lies in the design of neural algorithm. The neural algorithm that has been chosen to train the secret data bits and selected image bits, which has to be transacted through a secured channel between the source and destination. This makes the steganography process that hides the data in a more efficient manner. The neural algorithm is designed with respect to the input patterns. The main advantage of this proposal is that the secret data is not transmitted as it is. The added advantage is that the cipher text generated depends on the design of neural algorithm. Different algorithms are available for digital image steganography both in the spatial and transform domain like LSB substitution, OPAP, Pixel indicator technique, F5 etc.
Tax Policy and Firms' Financing Decisions: Empirical Evidence from the Dominican Republic

Numerous studies have tried to explain the financial behaviour of firms based on different theories. Despite the vast and rich literature, only in the last decade has attention also been focused on emerging economies. In the first place, the purpose of this paper is to investigate the determinants of the capital structure in an emerging economy, such as that of the Dominican Republic, testing the sustainability of the trade-off and pecking order theories. Secondly, we also investigated the impact of tax policy on the financial behaviour of businesses. In this perspective, this study overcomes the distorting problems associated with estimating the tax variable, as it uses data from each company's tax returns. The data were provided by the Ministry of Finance to the World Bank as part of a collaboration on the analysis of fiscal policy. A fixed-effects (FE) estimation technique has been employed to analyse the financial structure of companies. Overall, the results show that the individual determinants have a strong ability to explain the capital structure of companies, also highlighting that, in some cases, the fiscal variable influences the financial behaviour of
Long and Short Run Relationship Between Agricultural and Industrial Sectors’ Growth in Ethiopia Economy: Application of Co-Integration and Error Correction Model

The objective of this paper was to examine the long run and short run impact of agricultural sector on the industrial sector and to determine the direction of causality in Ethiopia economy using annual time series data ranging from 1991-2015 obtained from the World Development Indicators (WDI) database. The time of analysis related was to the adoption of agricultural led industrialization (ADLI) strategy to bring food security, poverty reduction, and rapid economic growth objectives in country. The result of the Johansen Co-integration test showed that data were integrated of ordered one in both trace, and max-trace statistical tests showed that there was strong long run equilibrium relationship between agricultural and industrial sectors outputs. The Johansen error correction model (ECM) indicated that agricultural series output has long run significant and positive impact on industrial sector series output but not vice versa. In the long run, increase in agricultural sector’s by one percent, being other factors held constant, the marginal industrial sector output increase by 3.39% due to multiplier effect. Granger pair wise causality test revealed that there is unidirectional causality from industry to agriculture sector. In the long run, growth comes from agriculture to industry and in the short run; agricultural growth is caused by industrial growth. Therefore, the adoption of ADLI strategy should be strengthened the sectors forward and backward linkages to bring balance, and rapid sectorial growth to support the entire economic growth in the country.
Washi: Understanding Japanese Paper as a Material of Culture and Conservation

The Book and Paper Group Annual 37 (2018) 77 Papers presented at the Book and Paper Group Session, AIC’s 46th Annual Meeting, May 29-June 2, 2018, Houston, Texas are in conference proceedings or European journals that may be more difficult for North American conservators to access. While much of the literature is quite dated, new and exciting research has been published in the last four years. Older publications, especially those discussing the traditional methods and history of washi are still relevant and valuable. However, the findings in resources related to washi permanence for use in conservation may not be reliable for the papers available today, although they do serve as records that may assist future researchers in how washi quality may have changed over time. Publications on washi can be separated into three categories: Washi Manufacturing—literature describing the papermaking procedures and its cultural context (Hunter 1943; Hughes 1978; Barrett 1983; Masuda 1985; Turner 1998; Mizumura, Kubo, and Moriki 2015; Colbourne and Hori 2015; Mizumura and Moriki 2017). Examination and Identification–literature that establishes characteristics differentiating washi from other kinds of paper or other kinds of washi (Collings and Milner 1978; Nicholson and Page 1988; Koestler, Indictor, and Fiske 1992). Quality Assessment–literature investigating the quality and aging characteristics of washi and the implication for conservation uses (Murphy and Rempel 1985; Inaba and Sugisita 1988; Uyeda et al. 1999; Inaba et al. 2002; El-Esseily and Inaba 2004; Calvini, Gorassini, and Chiggiato 2006). Even with the more recently published articles on the subject, there is still limited information that would help conservators assess washi quality from a conservation standpoint without use of costly and sometimes inaccessible advanced technical analysis. The aim of this paper is to review traditional papermaking processes and the cultural importance of washi. Methods for examining washi will also be discussed to guide selection of high quality washi for treatment relying on touch, sound, and transmitted and raking light.
Determination of Aromatic Amines in Wastewater Samples by High Performance Liquid Chromatography/Mass Spectrometry

A new method for the determination of aromatic amines,including benzidine,aniline,p-toluidine,p-nitroaniline,and α-naphthylamme,in wastewater was developed by high performance liquid chromatography/mass spectrometry.The chromatographic separation was carried on a Kromasil C18 column by using methanol-5 mmol/L ammonium formate buffer(pH=3.0) as mobile phase at a flow rate of 1 mL/min with a gradient elution mode and split sampling.The mass spectrometric quantitative analysis based on selective ionic measurement + by electro-spray ionization in positive mode.The calibration curves for the above aromatic amines were linear within the range of 7.03~281.30 μg/L,10.65~213.10 μg/L,11.91~238.20 μg/L,12.39~247.90 μg/L and 14.55~291.10 μg/L,respectively.The average recoveries were 92.7%~101.4% for the spiked samples.The detection limits(S/N=2) varied from 1.7 μg/L to 3.2 μg/L.The results show that the method has high sensitivity,simple pretreatment and wide linear range.It can be used as a fast and sensitive analysis method for the above aromatic amines in wastewater samples.
A method of workpiece location based on improved generalized Hough transform

In order to solve the problem that the workpiece is not easy to identify in the complex environment in the industrial processing, sorting and other automatic production links, a workpiece positioning method based on Improved Generalized Hough transform, also known as eif-ght, is proposed. In order to solve the problem of large time consumption and high memory consumption of traditional generalized Hough transform in target detection, this paper uses the rotation invariant feature angle formed by any two edge points in the image as the R table index under the condition of image preprocessing to realize the representation of target shape, and uses particle swarm intelligent evolutionary algorithm to speed up the search The final target is determined by similarity measurement. The experimental results show that when the workpiece rotates and shifts, and in the complex environment with noise, local occlusion, nonlinear illumination and so on, it can achieve stable and efficient positioning.
Generalized Attitude Model Identification of a Quadrotor

This paper studies the generalized attitude model (GAM) identification of a controlled quadrotor by using flight experimental data. The GAM describes the dynamics of the quadrotor and its driving motors. Its mechanism analysis will be first carried out for guiding the parametrization of its estimation model. Before the prediction error method (PEM) is applied on the GAM identification, the involved closed-loop identifiability problem is addressed. Finally, the accuracy of the estimated GAM is validated by comparisons of Bode diagrams and controller performances achieved by a redesigned robust controller.
The Railway Detection via Adaptive Multi-scale Fusion Processing

One of the main problems for safe autonomous driving vehicles that have not been solved completely is the high-precision and timely lane detection. In this work, we present a novel operator for railway detection to settle these tasks based on lane detection for the first time, called adaptive multi-scale fusion Sobel operators. The new operators can eliminate the noises generated by the environment in the railway image and derive more integrated edge feature information from the 0°, 45°, 90°, and 135° detection via 4 matrixes of 3 * 3 operators for permutation and summation. The image processing for railway detection includes the preprocess for images, railway edge detection, and track line polynomial fitting. Our experiment has validated that this improved detection method has realized the high accuracy and efficiency for rail detection. The dynamic rail detection and identification in the video of the railway track prove that this method has a significant effect on the left and right curved railway detection. It has good robustness and applicability.
Design and research on the adsorption system for self-regulating unmanned cleaning aircraft

Cleaning robot is one of the main research directions in the field of glass curtain wall cleaning at present. It has important theoretical research significance and practical application value in high altitude work tasks such as glass curtain wall cleaning and crack detection. At present, cleaning robots are prone to reduce their working stability due to the dynamic uncertainty of the high-altitude wind field environment, and even fall from the sky in serious cases, which greatly affects the safety of high-altitude operation. Therefore, an adsorption system applied to unmanned cleaning aircraft is proposed in this paper. The system has two advantages: (1) through the adjustment of the center controller, the system can be detected in dynamic environment according to the parameters change, the influence of adsorption force to adjust output parameters, the corresponding mechanism, control the automatic adjusting system surface adsorption, are keeping their reasonable adsorption range, thus ensuring the system stability; (2) When the adsorption force adjustment parameter exceeds the adjustment threshold, the system will automatically start the motor to make the rotor work and prevent the cleaning equipment from falling, so as to improve the safety performance of the system.
Research on Arrhythmia Classification Method Using Optimized Probabilistic Neural Network

Aiming at the classification difficulty of complex and diverse ECG signals, this paper proposes a feature extraction method based on standard deviation. This method solves the problems of multi-dimensional, diverse, high similarity and the difficulty in extracting main features effectively of ECG(electrocardiogram, ECG) signal features. In addition, this method overcomes the difficulty of low classification accuracy because of large differences in ECG signals of the same type among different patients. This paper adopts optimized probabilistic neural network methods to achieve automatic classification of arrhythmia. First, the standard deviation of the dimensions of each sampling point of the ECG signal would be calculated and sorted by size. Second, the first m dimensions as the feature dimensions of arrhythmia would be extracted. After that, the probabilistic neural network would be used to train and classify feature dimension data. Finally Bayesian Optimization(BO) method would be used to optimize the parameters globally. In the experiment of the MIT-BIH arrhythmia database, the arrhythmia data was divided into 5 categories and verified, experimental results show that the correct rate of classification of the arrhythmia data of patients reached 99.67%, which proved the effectiveness of the method in this paper.
The Impact of Voltage Stability Constraint L-Index on Power System Optimization Base on Interior Point Algorithm by Considering the Integration of Renewable Energy

Renewable energy (RE) generation including wind and solar farms has experienced significant growth due to the challenge of climate and energy crisis. High penetration of RE affects system stability and generation cost optimization. In this paper, voltage stability L-index is proposed as the constraint of the primal-dual interior point method for optimal power flow by considering the integration of wind and photovoltaic cell power on system. L-index is used in this study to indicate the voltage security while renewable energy is prefixed into power system to build a new (REL-OPF) formulation that can consider the voltage stability margin and generation cost of the power grid. Weibull and Beta probability density functions are applied to determine the outputs of wind and photovoltaic power generation respectively. This model has the advantage that there is no need to calculate the critical point and could obtain the demanded voltage security level by adjusting the upper limits of indicator L constraints. The optimal solution can concurrently satisfy both the voltage security and the economical demand for power systems. The overall problem is simulated under coding written in MATLAB environment. The results obtained from regulating the upper limit of voltage stability constraint on IEEE30-bus has shown that the attention of RE generations into the system leads the fuel cost objective to decrease randomly as well as enlarge the distance of stability to a critical point with faster convergence.
Design of a proportional integral derivative controller of temperature regulated for a nursery

This article describes the design and simulation of a proportional integral derivative PID controller that operates a proportional control valve to allow the flow of hot water to the radiant floor of a pig farm to maintain the required temperature. In the development of the project physical and mathematical concepts are required for controlling, the temperature oscillations in the range of 25 °C to 35 °C and the heat flux through the radiating surface of the floor, as well as analyzing the parameters involved for the development of the control system; In the control system design the characteristics and parameters involved in the pigs rearing by means of corral were identified; later the thermal analysis of the heating system integrated into the radiant floor that supplies heat to maintain the temperature was carried out, then the response of the temperature control system was simulated in the Scilab software and finally, the programming of the proportional integrative control was carried out. The design considers using gas generated in a biodigester to transfer thermal energy to the heating water that circulates through the floor, transferring heat to the brood module until it reaches and maintains the desired temperature using a control system that involves a proportional valve program in Arduino. The entire system was simulated by means of software including the gas and water circuits according to the heat transfer flow required to maintain the controlled temperature inside the module. The developed design allows controlling the heat flow to maintain the required temperature, stabilizing the process in 20 minutes.
Digital multi-agent system for simulating natural fire fighting processes

A system for modeling and supporting decision-making on the use of forces and means to eliminate wildfires, based on a digital model, implemented in the software “Taiga-Analyst”, is proposed. The system works on the basis of agent-based simulation and allows you to select forces and means to fight a fire, simulate its propagation and elimination with reference to a digital terrain map using a geographic information system. The possibilities and scope of the “Taiga-Analyst” system are described. A decision-making scheme for fighting natural fires is shown, and the use of the system in the process of training fire safety specialists is described.
Time series and stochastic differential equations as a tool to model the volatility of an asset

In the problem of estimating the prices of electricity markets, different forecast models have been proposed for the short term, among the most outstanding are the works by Francisco Nogales, which uses autoregressive integrated moving average methodology to analyses time series in the California market. Peninsular Spain. Nogales and Contreras use time series models applied to the markets of California and Spain, the applied series were carried out to estimate the hourly price of the following day using two methodologies, the first a dynamic regression and the second transfer function models. In he proposes a prediction based on Autoregressive conditional heteroscedasticity models generalized conditional autoregressive heteroscedasticity Rabbit use the wavelet transform to decompose the data series, then applying an autoregressive integrated moving average model to the transformed series, taking advantage of the existing advantages in the domain of the frequency. The techniques have a high correlation with problems of physics which can be approached in a similar way, we must highlight the fact of using stochastic differential equations which are modern techniques in mathematics and physics.