Miracle-dz/UniFAR-FTUs huggingface dataset:
Newton-based Policy Search for Networked Multi-agent Reinforcement Learning

Newton’s method is a standard optimization algorithm, characterized by a fast rate of convergence and used in many popular approximated methods that use second-order information. Despite its well understood theoretical properties, quadratic convergence rate and extended applications, Newton’s method is seldom used for policy optimization in Multi-Agent Reinforcement Learning problems. In this work we investigate a distributed Newton consensus scheme for performing policy search in a networked cooperative environment, where the agents are endowed with private local rewards, though they aim to collaborate for maximizing the network-wise averaged long-term return. In the proposed algorithm, the agents seek for the parameters of the optimal global policy by locally computing an approximated Newton’s direction for the global objective function, and sequentially update it in a distributed fashion by means of an average consensus procedure. The strategy is purely policy-based and does not involve any representation of the global value-function. We analyse the computational and theoretical properties of the algorithm and prove, under suitable assumptions, global converge to the true maximizer. Additionally, we provide convergence guarantees also under finite-sample conditions. Beside the theoretical properties, we perform numerical experiments showing the validity of the approach and highlight its improved convergence speed when compared to a simpler first-order distributed method.
Evaluation of nodes distribution for linear terrain objects to calculate the optimal parameters of coordinate reference systems in terms of the Republic of Chile.

The article focuses on the need to evaluate the distribution of coordinates of the object nodes and their filtering (discharge) in order to implement algorithms for calculating the optimal parameters of projection coordinate systems. To solve this task, it is proposed to use the uniform distribution function, the value of which characterizes the concentration degree of the nodes that form the contour of linear objects. At the same time, the Chi-square criterion, as an estimation indicator, allows implementing iterative procedures for combining nodes and generalizing parts of objects to approximate the initial data to the uniform distribution. Studies have shown that it leads to the reduction in the excess concentration of nodes of linear terrain objects, which negatively affects the calculation of optimal parameters for coordinate reference systems. The paper also considers the examples of coordinate systems parameters, which are, moreover, implemented on the basis of oblique map projections, the use of which is possible for solving a wide range of engineering tasks for transport facilities, agriculture and environment studies of the Republic of Chile. The article also provides a graphical comparison of the suggested single 6-degree zone for the specified class of projections with the SIRGAS-Chile coordinate system using the Universal Transverse Mercator coordinate system (UTM Zone 18 and Zone 19). In conclusion the author presents the data that prove the necessity for the mandatory evaluation of the uniformity of initial geodata distribution in order to find the best projection parameters.
Shear rate dependence and the effect of resistivity in magneto-rotationally unstable, stratified disks

We study the eect of resistivity and variation of shear rate, q = dl og=dR, on the magneto- rotational instability in stratied disks. Special attention is paid to dynamo -action and transport properties of the flow. The 3D magnetohydrodynamical simulations are performed in the local shearing-box approximation employing the code NIRVANA. Due to the chosen type of vertical boundary condition a mean azimuthal magnetic eld is generated which is related to dynamo-action. The corresponding-parameter is negative (positive) in the northern (southern) disk hemisphere. This result is independent of q ranging between 0: 6a nd 1:5 and independent of the amount of diusivity. The magnitude of typically declines with decreasing q. We suggest a natural limit in the vicinity of q =0 : 6b elow which-action may be suppressed completely. Resistivity has a signicant influence on the magnetic energy level of the nal state. It is reduced for decreasing magnetic Reynolds number,Rem ,a s one might expect. However, the magneto-rotational instability is able to sustain an angular momentum transport of sucient amount against diusion even for the most diusive case we considered, with Rem = 200. The Shakura- Sunyaev parameter in this case is roughly 1=3 of that of the non-resistive model with the dominant contribution provided by the Reynolds stress rather than Maxwell stress. The dynamo -eect is found to vanish for strong dissipation.
THE BI-PERIODIC FIBONACCI-HORADAM MATRIX

The Fibonacci sequence has been generalized in many ways. Some generalizations are done by altering the recursive equation while others are obtained by changing its initial values. In this work, we look at particular generalizations of this sequence by incorporating a periodic parameter in the ﬁrst term and a constant coeﬃcient in the second term of the recursive formula. We study two sequences given by G n +1 = p n G n + qG n − 1 and H n +1 = p n +1 H n + qH n − 1 , where p n = a when n is odd, and p n = b when n is even, with initial values G 0 = 0, G 1 = 1, H 0 = 2, H 1 = a . Here, a, b, and q are nonzero real numbers. We call these sequences the bi-periodic Fibonacci-Horadam sequence and the bi-periodic Lucas-Horadam sequence, respectively. The initial values correspond to those of the bi-periodic Fibonacci sequence and bi-periodic Lucas sequence, described in the works of Edson et al. (2009) and Bilgici (2014). In contrast to the use of generating functions, elementary matrix analysis will be used to formulate identities of the said new recursions. The bi-periodic Fibonacci-Horadam matrix G is constructed which is then used in the derivations of the diﬀerent properties of the bi-periodic Horadam sequences including summation identities.
Guaranteed Cost Control for Fuzzy Bilinear Systems with Uncertain Parameters

The main theme of this paper is to present robust guaranteed cost control laws for a class of fuzzy bilinear systems (FBS) with parametric uncertainties. First, the piecewise Lyapunov function (PLF) method is utilized to design a fuzzy controller, which ensures the robust asymptotic stability of the closed-loop system, and then the robust guaranteed cost control law is also proposed. Second, based on the Schur complement and some variable transformations, some sufficient conditions are derived to guarantee the stability of the overall fuzzy control system via linear matrix inequalities (LMIs). Finally, a numerical example is utilized to demonstrate the validity and effectiveness of the proposed control scheme.
A scenario solution to state-feedback controller design for discrete-time linear systems subject to probabilistic constraints

This paper deals with discrete-time linear systems affected by an additive stochastic disturbance and subject to input and state constraints. We consider the problem of designing a linear state-feedback control law so as to minimize a cost function while guaranteeing the satisfaction in probability of the constraints by the steady state solution. The problem can be formulated as a chance-constrained optimization program with constraint satisfaction depending on the stationary state distribution, which in turn depends on the controller gain. A data-driven solution is proposed where constraints are imposed on a finite number of disturbance realizations of finite length. By leveraging the new wait-and-judge paradigm of the scenario approach to address the intrinsic nonconvexity of the resulting optimization problem and by explicitly accounting for the introduced approximation error when using finite length disturbance realizations to approximate the steady state, chance-constrained feasibility of the proposed solution is proven.
An exact robust hyperexponential differentiator

A simple differentiator is proposed, which is modeled by a second order time-varying linear differential equation. It is shown that for any signal of interest, whose second derivative is an essentially bounded function of time, the differentiation error converges to zero with a hyperexponential rate (faster than any exponential). An implicit discretization scheme of the differentiator is given, which preserves all main properties of the continuous-time counterpart. In addition, the differentiation error is robustly stable with respect to the measurement noise with a linear gain. The efficiency of the suggested differentiator is illustrated through comparison in numeric experiments with popular alternatives.
High-velocity drag friction in dense granular media

We study drag force acting on an obstacle in granular media, focusing on a high-velocity region where only a few direct studies are available. The granular media are two-dimensional and consist of small-sphere particles. A larger-disk obstacle moves in the medium at different constant speeds. The drag force is found to be proportional to the square of the velocity. We explain the observed relations by developing original scaling arguments and by demonstrating a clear data collapse. As a result, we conclude that the friction we observed is physically different from a hydrodynamic inertial friction, which has been discussed in dilute granular flows and in impact experiments. The high-velocity drag friction observed in this study may be attributed to another mechanism, where the formation of the dynamical force chains plays a crucial role.
Integrated Segmentation and Subspace Clustering for RSS-Based Localization under Blind Calibration

Indoor localization is important for many location- based services. The fundamental challenge is the high deployment cost for device, infrastructure, and calibration. This paper develops a blind calibration approach for received signal strength (RSS)-based localization. The essential idea is to employ a device that visits each region exactly once in an indoor area to complete a blind data collection process without recording the route, locations, and timestamps. Thus, the key challenge is to cluster the blind training data into groups and extract the key features to identify the location regions. Classical clustering algorithms fail to work as the data naturally appears as non-clustered due to mutipaths and noise. In this paper, an integrated segmentation and subspace clustering method is developed to exploit both the sequential data structure from the blind data collection process and the signal subspace structure due to the segmented propagation environments. Based on real measurements from an office space, the proposed scheme reduces the region localization error by roughly 50% from a weighted centroid localization (WCL) baseline. In addition, the performance is also comparable to k-nearest neighbor (KNN) and support vector machine (SVM) that require labeled data for calibration.
Channel Measurement and Characterization at 140 GHz in a Wireless Data Center

The Terahertz (0.1-10 THz) band wireless data center networks (DCNs) are promising to provide high data rates and low latency for next-generation cloud applications. However, one research gap that is still existed is the lack of measurement data and thorough characterization of the THz wave propagation in data centers. To address this problem, in this paper, two sets of measurement campaigns are conducted in a data center scenario at 130–140 GHz band, by using a vector network analyzer (VNA)-based channel sounder system with different receiver heights. The measured data is further processed to extract the multi path components (MPCs) and classify the MPCs into clusters. Furthermore, the channel characteristics, including the path loss, shadow fading, K-factor, delay and angular spreads are calculated and analyzed. Clustering results and MPCs propagation are analyzed and examined in light of the real geometry in the data center. Interestingly, comparison with measured results in meeting room scenarios at 140 GHz shows that the reflections and scattering from metal racks in the data center are more significant, resulting in lower path loss, smaller K-factor, and larger delay spreads. The measured results in this work substantiate guidelines for system design of THz wireless DCNs.
MuSigRDT: MultiSig Contract based Reliable Data Transmission in Social Internet of Vehicle

Social Internet of Vehicle (SIoV) has emerged as one of the most promising applications for vehicle communication, which provides safe and comfortable driving experience. It reduces traffic jams and accidents, thereby saving public resources. However, the wrongly communicated messages would cause serious issues, including life threats. So it is essential to ensure the reliability of the message before acting on considering that. Existing works use cryptographic primitives like threshold authentication and ring signatures, which incurs huge computation and communication overheads, and the ring signature size grew linearly with the threshold value. Our objective is to keep the signature size constant regardless of the threshold value. This work proposes MuSigRDT, a multisignature contract based data transmission protocol using Schnorr digital signature. MuSigRDT provides incentives, to encourage the vehicles to share correct information in real-time and participate honestly in SIoV. MuSigRDT is shown to be secure under Universal Composability (UC) framework. The MuSigRDT contract is deployed on Ethereum's Rinkeby testnet.
Magdroid: An IoT-Enabled Environment-Aware Electrical Safety Assistant

In this work, we propose an environment-aware electrical safety assistant using smartphones in pervasive domains like industry, homes, and healthcare. Conventional methods involve using eye shields, gloves, finger guards, and safety toe shoes. We depend on IoT-based solutions and propose Magdroid, an autonomous and standalone smartphone application that detects any electrical anomaly around the user and alerts all the users in the network. Magdroid supports edge computing and provides in-app inferences without any dependency on remote servers. It extracts the in-built magnetometer readings to detect any electrical anomaly in the environment. Since the readings vary with the environments, Magdroid first senses and then uses a cascaded deep learning technique to predict the electrical anomaly around the smartphone. We use two Convolution Neural Network (CNN) architectures and cascade the inference of one with the input of another to generate efficient results for detecting electrical anomalies that are particular to that environment. The first model achieves a test accuracy of 98.97% for the prediction of the environment and the cascaded CNN achieves a test accuracy of 81.88% with 7.82% and 37.27% loss, respectively. Additionally, Magdroid is a low resource-consuming application that utilizes 8% CPU and 126.MB memory of the smartphone.
Abundances in the Neutral Interstellar Medium of I Zw 18 from Far Ultraviolet Spectroscopic Explorer Observations

We report on new FUSE far-UV spectroscopy of the most metal-poor blue compact dwarf galaxy, I Zw 18. The new data represent an improvement over previous FUSE spectra by a factor of 1.7 in the signal-to-noise ratio. Together with a larger spectral coverage (λλ = 917-1188 Å), this allows us to characterize absorption lines in the interstellar medium with unprecedented accuracy. The kinematics averaged over the large sampled region shows no clear evidence of gas inflows or outflows. The H I absorption is interstellar with a column density of 2.2 × 1021 cm-2. A conservative 3 σ upper limit of 5.25 × 1014 cm-2 is derived for the column density of diffuse H2. From a simultaneous fitting of metal absorption lines in the interstellar medium, we infer the following abundances: [Fe/H] = -1.76 ± 0.12, [O/H] = -2.06 ± 0.28, [Si/H] = -2.09 ± 0.12, [Ar/H] = -2.27 ± 0.13, and [N/H] = -2.88 ± 0.11. This is in general several times lower than in the H II regions. The only exception is iron, whose abundance is the same. The abundance pattern of the interstellar medium suggests ancient star formation activity with an age of at least 1 Gyr that enriched the H I phase. Around 470 SNe Ia are required to produce the iron content. A more recent episode that started 10 to several hundred megayears ago is responsible for the additional enrichment of α-elements and nitrogen in the H II regions.
An Analysis of Convergence Properties of Finite-Time Homogeneous Controllers Through Its Implementation in a Flexible-Joint Robot

A study of the stability of interconnected homogeneous systems, affected by singular perturbations, is presented by means of the implementation of finite-time composite control in a single-link flexible-joint robot. Previous results suggest that the implementation of finite-time convergent controllers leads to the arising of chattering. Now, throughout a practical example we show that the design of a controller making the whole system homogeneous avoids the undesired chattering and recovers the ideal finite-time convergence properties. Regrettably, information of the states of the fast dynamics is not commonly available, then the proposed strategy is not applicable at all. Nevertheless, the main interest of our study lays in the expansion of the panorama for a better understanding of the causes of chattering, which contributes to the development of chattering reduction techniques, and has attracted a lot of attention, nowadays.
Value-directed information search in partner choice

It is a widely held view that people rely on incomplete information to find a relationship partner, resulting in non-compensatory choice heuristics. However, recent experimental work typically finds that partner choice follows compensatory choice strategies. To bridge this gap between theory and experimental evidence, we characterize the mate choice problem by distinguishing the information search process from the evaluation process. In an eye-tracking experiment and a MouseLab experiment, we show that people display strong value-directed search heuristics in response to all types of cues and that the magnitude of value-directed searches increases with cue primacy. Cue primacy also explains the interaction effect of cue type and participant sex on the extent of valued-directed search. We further argue that value-directed searching does not necessarily lead to non-compensatory choice rules but may serve compensatory decision-making. Our results demonstrate that people may adopt remarkably smart search heuristics to find an ideal partner efficiently.
Evaluation of broadband and hyperspectral IR sounders

The High spectral resolution infrared radiances from the Atmospheric InfraRed Sounder (AIRS) onboard the NASA's Earth Observing System (EOS) Aqua satellite are used to retrieve atmospheric temperature and water vapor profiles, etc. Evaluation of these retrieved parameters is performed by a comparison with the operational products from current Geostationary Operational Environmental Satellite (GOES) sounder, radiosonde observations (RAOBs) at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) site in Oklahoma, United States. Comparisons show that the physical-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error (RMSE) of 1 K on average for temperature profiles above 850hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite (GOES) sounder when comparing AIRS sounding retrievals with the operational GOES sounding products. The advancement of hyperspectral IR sounder in deriving atmospheric parameters over the current broadband IR sounder is demonstrated and analyzed
Earnings Management: A critical Literature Review

Purpose: The purpose of this study was to takes a critical literature review of earnings management with the aim of establishing research gaps and areas for further research. Methodology: The study employed meta-analysis technique by relying on findings from prior studies to draw conclusion. The study reviewed empirical evidence from both international and local context covering the period 2014 to 2020. Findings: The study established both accrual based and real earnings approach techniques were used in detection of earnings management. With majority of studies suggesting Jones modified model as the most accurate, in detecting earnings management. However, the studies were inconlusive on the motivation for earnings management. The results on the relationship between earnings management, corporate governance and modified opinion were mixed. Implications: The findings that links earnings management, modified audit opinions and corporate governance will be of interest to policy makers and those charged with corporate governance on how it can be constrained. Value of Study : The study contributes to litelature by evaluating theoretical and empirical evidence. The study also has helped to identify research gaps, how to operationalize and test variables.
Summary Generation using NLP Techniques

—Due of the large amount of information and electronic documents available on the internet, it is impossible for a human to study, examine, and analyze this material. The main concept because the core idea of summarization allows humans to swiftly read the summary of a large amount of content and makes a decision whether or not to go deeper into the intricacies. Detailed summaries create a summary by extracting a certain collection of sentences from a document in which NLP approaches like Genism, Text rank, Rule based and Pegasus can be used on a single document or several documents. Thereupon, synopsis generation is the charge of generating incisive summaries unescorted by human assistance while conserving the genuine sense of the overlong document.
AMBIENT SOUND IN HEALTHCARE SETTINGS AND ITS EFFECTS ON PATIENTS AND STAFF: A
SYSTEMATIC REVIEW

Sound can affect patients, staff, and visitors in healthcare settings in many ways. The purpose of this review was to synthesize and investigate sound in healthcare settings and the effects of these sounds. Relevant studies published between January 2017 and June 2022 were searched through a systematic literature review process using the Google Scholar, PubMed, Scopus, Web of Science, and Wiley Online Library databases. A total of 25 papers met the inclusion criteria. The study results cover three main areas: perceived sound sources and sound levels; associations between healthcare settings and sound; and sound’s effects on patients and staff. This study shows that in terms of sound, the environment in hospitals, nursing homes, and outpatient centers is boisterous. Among other findings, associations were identified between sound and types of healthcare services; activities and behaviors; architectural features and materials; and mobile communication devices. Most studies report that sound has adverse effects on patients and staff, while nursing home-related studies report the positive attitudes of residents to musical activities. By evaluating the multiple sound-related solutions available, this review indicates that future research in this area should focus on the long-term effectiveness of interventions and the provision of standards of practice for optimal sound environments, based on different healthcare settings.