Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for analysis and synthesis of fuzzy linguistic control systems

Fuzzy Linguistic Control(FLC) may be viewed as a knowledge based control strategy that can be used when the dynamic characteristics of the plant or the associated control objectives are not sufficiently well posed to warrant the, at least immediate, application of conventional control techniques. Alternatively, in these situations one may opt for a heuristically designed control strategy that relies on empirically acquired knowledge regarding the operation of the process. This knowledge cast into linguistic or rule based form constitutes the core of a fuzzy linguistic control system. In other words, the control law, instead of being stated as an analytic function of the process output (or state for that matter), is composed of condition $\to$ action rules that capture, in an approximate sense, the empirical knowledge or know-how necessary to effectively control the process. This heuristic approach to control design raises important issues regarding the stability and reliability of fuzzy linguistic control systems. In this connection, the purpose of this dissertation is twofold. First, we present an approach to the analysis of stability of fuzzy linguistic control systems that is based on Lyapunov's Direct Method and as such offers sufficient conditions, which if met, guarantee global asymptotic stability of the system under consideration. Second, we will present an alternative framework for analysis, as well as synthesis, of fuzzy linguistic control systems that is intended to bridge the gap between this type of control strategy and conventional control techniques. Specifically, by parametrizing the characteristic functions of fuzzy subsets describing the linguistic terms used in the definition of the control rules, we develop an analytic formulation of the control scheme, which is then used to derive sufficient conditions for asymptotic stability of the closed loop dynamic system operating under fuzzy linguistic control. In this process, we will also establish a connection between fuzzy linguistic control and a class of nonlinear control schemes, namely those with piecewise linear characteristics. Furthermore, we present a new interpretation of fuzzy linguistic control that helps explain how certain types of nonlinearities, such as asymmetric response characteristics, can in effect be canceled by appropriate formulation of control rules. Finally, we will suggest how fuzzy linguistic control, in general, can be used to deal with other commonly occurring nonlinear behavior in industrial processes such as actuator saturation, nonlinear sensor behavior, and/or operating regime dependent variations in the response characteristics of the process.
MEANS AND MECHANISMS OF INFORMATION AND COMMUNICATION IN KNOWLEDGE MANAGEMENT IN ORGANIZATIONS

Knowledge management in organizations is an issue that has been strengthened from the realization of processes in support of digital and traditional tools. The result of the study that sought to know the availability of information and communication technologies in knowledge management in Bogota companies is presented here. The investigation had as informants 386 officials of public and private companies, to whom an instrument was applied. Among the results, it was obtained that the level at which electronic media for CG and traditional mechanisms for CG are found is high at 77.5% and 57.3% respectively, 21.2% and 40.9% average, as well as, for two variables, low by 1.3% and 1.8%. The relationship between ICT and knowledge management is positive and strong.
Design of asynchronous federated learning incentive mechanism

: Federated learning has been widely paid attention as a new type of distributed machine learning that can protect data privacy and ensure data security. Asynchronous federation learning, a variant of traditional federation learning, can effectively improve model training efficiency. The introduction of incentive mechanism can help asynchronous federation learning to improve model training utility effectively. A federated learning incentive mechanism is constructed using the Stackelberg game, which optimizes the central server and data owner utilities, respectively, of the Stackelberg game. Based on this, we derive the equilibrium solution of the whole game, and finally analyze the feasibility of the model by arithmetic examples to obtain the optimal incentive effect.
Metformin Affects Plasma Levels of Soluble Leptin Receptors in Type 2 Diabetes Mellitus and Metabolic Syndrome Patients

Background: Obesity and insulin resistance elevate plasma leptin, while it lowers plasma levels of soluble leptin receptors (sOB-R). Objectives: To measure the levels of sOB-R in patients with type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) and compare it to healthy controls. The study also aimed to investigate the inﬂuence of metformin on the levels of sOB-R in patients with T2DM and MetS. Materials and methods: A cross-sectional study was conducted on 66 participants (33 patients and 33 controls). Patients were divided into two groups; Group I included 17 newly diagnosed T2DM patients, and Group II included 16 patients with MetS. Patients were studied before and 3 months after treatment with 850 mg metformin treatment. Group III included 33 non-obese healthy individuals as a control group. Measurements such as height, weight, waist circumference, hip circumference, blood pressure examination, and biochemical tests including fasting blood sugar, HbA1c, total cholesterol (Ch), triglyceride, high-density lipoprotein (HDL), insulin level, plasma sOB-R levels were performed. Ch/HDL ratio, non-HDL cholesterol, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), Waist Hip Ratio (WHR), and Body Mass Index (BMI) were calculated. Results: No statistically signiﬁcant diﬀerence was found among the groups regarding sOB-R levels initially, but after metformin treatment, T2DM patients showed a signiﬁcantly higher level (10.19 ng/ml). There was a signiﬁcant increase in the levels of sOB-R after metformin treatment, as it increased from 7.82 ng/ml to 10.19 ng/ml in T2DM, and from 6.92 ng/ml to 7.82 ng/ml in MetS patients. Conclusion: Metformin signiﬁcantly increases the plasma levels of sOB-R in T2DM patients but only slightly increases these levels in MetS patients.
Approximate solutions and scalarization in set-valued optimization

Abstract Certain notions of approximate weak efficient solutions are considered for a set-valued optimization problem based on vector and set criteria approaches. For approximate solutions based on the vector approach, a characterization is provided in terms of an extended Gerstewitz’s function. For the set approach case, two notions of approximate weak efficient solutions are introduced using a lower and an upper quasi order relations for sets and further compactness and stability aspects are discussed for these approximate solutions. Existence and scalarization using a generalized Gerstewitz’s function are also established for approximate solutions, based on the lower set order relation.
Robust observer‐based stabilization of Lipschitz nonlinear uncertain systems via LMIs ‐ discussions and new design procedure

This paper presents a new observer‐based controller design method for Lipschitz nonlinear systems with uncertain parameters and L2 ‐bounded disturbance inputs. In the presence of uncertain parameters, the separation principle is not applicable even in the case of linear time invariant systems. A state of the art review for uncertain linear systems is first presented to describe the shortcomings and conservatism of existing results for this problem. Then a new LMI‐based design technique is developed to solve the problem for both linear and Lipschitz nonlinear systems. The features of the new technique are the use of a new matrix decomposition, the allowance of additional degrees of freedom in design of the observer and controller feedback gains, the elimination of any need to use equality constraints, the allowance of uncertainty in the input matrix and the encompassing of all previous results under one framework. An extensive portfolio of numerical case studies is presented to illustrate the superiority of the developed design technique to existing results for linear systems from literature and to illustrate application to Lipschitz nonlinear systems. Copyright © 2016 John Wiley & Sons, Ltd.
Nonlinear system modeling and identification using tensor approaches

Nonlinear system modeling and identification constitute a key issue for almost all fields of application. This paper consists of two parts. In the first one, we give an overview of main nonlinear dynamic input-ouput models, including dynamic polynomial models, Volterra models, and block-oriented models. The link between block-oriented models and Volterra models is emphasized by giving explicit expressions of the Volterra kernels associated with Wiener, Hammertein, Wiener-Hammerstein, and parallel cascade Wiener models. In the second part of the paper, we show how block-oriented models can be estimated by means of tensor-based approaches. Some simulation results illustrate the effectiveness of the extended Kalman filter for identifying Volterra-PARAFAC models.
The Thin Film Evaporation of R32/ R600 Mixture: A Molecular Dynamic Simulation

The utilization of mixed refrigerants in thermodynamic cycles is expected to improve the efficiency of the system. In the present paper, the evaporation behavior of the equimolar mixture of R32 and R600 on the copper surface is investigated by molecular dynamics approaches. The results denote that the evaporation process of the mixed R32/R600 liquid film can be roughly divided into the slow evaporation stage, stable evaporation stage and equilibrium stage. The evaporation rate of both R32 and R600 is maintained at a constant value during the stable evaporation phase, with the value of R32 being higher than that of R600. Besides, the evaporation of R32 and R600 is not synchronous. R600 enters both the stable evaporation phase and the equilibrium phase later than R32, indicating that the heat transfer thermal resistance of R600 is higher than that of R32. Furthermore, the three-dimensional vapor-liquid interface structure is obtained during the evaporation of the mixed R32/R600 liquid film. It is noticed that the undulation of the interface structure is greatest during the stable evaporation phase, where the vapor-liquid interface area is greater.
Synthetic Aperture Radar Image Generation With Deep Generative Models

A variety of machine learning approaches have been applied to synthetic aperture radar (SAR) automatic target recognition. The performances of these approaches rely strongly on the quality and quantity of training data. In real-world applications, however, it is challenging to obtain sufficient data suitable for these approaches. To alleviate this problem, a novel deep generative model for SAR image generation is proposed, which is an extension of Wasserstein autoencoder. The network structure and reconstruction loss function of the model have been improved according to the characteristics of SAR images. The experimental results demonstrate that our model is superior to other classical generative models in SAR image generation. The generated images can be directly used as training samples, thereby extending the training data set and improving the recognition accuracy.
No quarantine, is it safe to travel?

One of the sectors most affected by the Covid-19 pandemic is tourism, especially because of the quarantine policy. The quarantine policy is considered an effective strategy to prevent and control the transmission of COVID-19. Quarantine refers to efforts to identify exposure to Covid-19 in a person by segregating and restricting movement. The public hope that the tourism sector will soon improve with the elimination of the quarantine policy. The removal of the quarantine policy as a form of leeway is considered to be able to increase people's intention to travel and boost economic recovery. However, some experts argue that this policy is less effective because people still have concerns over the unexpected emergence of new variants of Covid-19. This explanatory study aims to analyze the perception of quarantine elimination effect on attitude and travel intentions. The study used a survey as the data collection method. The results showed that perceived risk negatively affects tourists' attitudes toward quarantine elimination policies and travel intentions. The tourism provider need to comprehend tourist perceived risk and capable to give valuable information to reduce the risk perception.
On the mathematical foundations of the statistical analysis in physics

The work of Ludwig Boltzmann on statistical mechanics has shown that a statistical analysis of subsystems of the universe needs to be embedded within a statistical analysis of the universe which above all is needed to explain the origin of low-entropy initial states. I aim to provide such an analysis. The main advantage of this account as compared to standard explanations is that it does not invoke a Past Hypothesis, i.e., it works without the assumption of a very special (atypical) state at the beginning of the universe. Instead everything is typical. To obtain this explanation, I relate a proposal of Carroll and Chen [2004], [2005] to the recent work of Barbour, Koslowski and Mercati [2013], [2015]. To draw the connection I introduce a notion of entropy for the Newtonian universe (which is a model of N particles moving through infinite space thereby attracting each other according to the Newtonian gravitational force law). I show that, with respect to this notion of entropy, the Newtonian universe is a Carroll-type universe, featuring a U-shaped entropy curve. This explains the observation of an entropy gradient, but it leaves us with an non-normalizable measure which cannot provide a statistical analysis. Next I deal with the statistical analysis. I show that the measure suggested by Barbour et al. is indeed the correct measure for the statistical analysis of the Newtonian universe. For that purpose I derive the formula which they use to construct the measure from the geometry of the underlying space, the space of physically distinct mid-point data. This space is obtained by reducing the standard phase space of the system with respect to the symmetries of translation and rotation, introducing an internal time parameter and finally using the dynamical similarity of the internal equations of motion. Once we got rid off all the redundant degrees of freedom, we are able to construct a normalizable volume measure in terms of which a statistical analysis can be made. From this we learn that typically at the point of minimal extension of the particles, the Big Bang of the Newtonian universe, the system is in a homogenous state, a state of low entropy. Hence, we got rid off the Past Hypothesis in the end. Having determined the reduced internal dynamics of the Newtonian gravitational system, we are able to address another topic: the evolution through the points of total collision. Whereas on absolute phase space the physical vector field turns singular at the points of total collision, this does not happen on shape phase space. Instead, the shape degrees of freedom can be evolved uniquely through the points of total collision, determining a unique way to combine two solutions on absolute phase space – one which ends at and one which starts at a total collision – to form one trajectory passing the singularity.
Fault estimation and observer-based fault-tolerant controller in finite frequency domain

In this paper, the problems of finite-frequency fault estimation (FE) and fault tolerant controller design are investigated for a class of systems subjected to both sensor and actuator faults. To begin with, by introducing an expanded state vector, the original system is transformed into a descriptor system, and then an unknown input proportional-integral observer (PI) is developed to provide state and FE, which avoids the overdesign problems occurring in the entire frequency domain. After this, based on reconstructed information, an observer-based fault-tolerant controller is designed to stabilize the closed-loop system even if it suffers from faults and disturbances. In addition, the sufficient conditions of the existence of the PI and fault tolerant controller are derived by linear matrix inequality (LMI) tools. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed techniques.
Social Interactions Leading Role in Adopting the Fintech: A Case of Banking Sector

The objective of this study is to analyze the client behavior regarding the acceptance of FinTech services in the banking sector. The assumption is that social connections have a stronger impact on the acceptance of FinTech services and technology. To achieve this objective, several banks in Pakistan providing FinTech services were targeted, and a convenient sampling method was used to distribute questionnaires to bank users. After screening the questionnaires, a total of 377 responses were analyzed. Structural Equation Modeling was employed to analyze the data, and the results indicated that customers are more likely to adopt FinTech services if they trust the services, and this trust is developed through positive word-of-mouth from their social network. Additionally, the study found that customer education is a crucial moderator, as higher education levels lead to more informed responses. Educated customers showed a greater intention to adopt FinTech services, especially when they received positive feedback from friends and family. Based on these findings, it is recommended that service providers in lower-developing regions focus on building trust and utilizing social networks to promote the FinTech culture.
A Dedicated Search for Low Frequency Radio Transient Astrophysical Events using ETA

Astrophysical phenomena such as self-annihilation of primordial black holes (PBHs), gamma ray bursts (GRBs), and supernovae are expected to produce single dispersed pulses detectable in the low end of the radio spectrum. Analysis of these pulses could provide valuable information about the sources, and the surrounding and intervening medium. The Eight-meter-wavelength Transient Array (ETA) is a radio telescope dedicated to the search for these pulses in an 18 MHz bandwidth centered at 38 MHz. ETA consists of 10 dual-polarized active dipoles providing an all-sky field of view. This thesis describes the results of a search campaign using ETA, namely, a Crab giant pulse (CGP) search. CGPs are already known to exist, and thus provide an excellent diagnostic for system performance. We found 11 CGP candidates in 14 hours of data. Although there has not been a single compelling detection (signal-to-noise ratio > 6), our analysis shows that at least a few of these candidates may be CGPs. We also explain the analysis preparation for PBH and GRB searches. Additionally, we describe the instrument and a software “toolchain” developed for the analysis of data that includes calibration, radio frequency interference (RFI) mitigation, and incoherent dedispersion. A dispersed pulse simulation code was developed and used to test the toolchain. Finally, improvements are suggested.
The assessment of daylight reflection from building envelopes

Buildings could influence surrounding microclimate with their envelope designs. Reflective surfaces on the building envelopes could reflect daylight to the neighbourhood and cause problems such as glare and overheating. For the surrounding drivers, pedestrians and building occupants in the area, the reflected sunlight from the building envelope becomes the bright spot in their view which results visual discomfort or impairment. For building envelope designs, it is important to analyse the effect of daylight reflection to the neighbourhood at design stage. This could reduce the risk of environmental problems and minimize the consequences cost after construction. A software tool to evaluate the reflected daylight from building envelopes has been developed. It is implemented on parametric design platform GRASSHOPPER using RADIANCE as background simulation engine. As shown in the case study, using the tool, the form of the assessed building envelope could be analysed and the critical areas around the assessed building including roads, pavements and façades of neighbouring buildings are examined for potential concentration of reflected daylight. Rich information is recorded for the critical areas: annual reflected solar radiation, period with irradiance value above threshold, origin of the reflected daylight on the assessed building envelope, etc. This information could help designers to optimize the form of the envelope and make façade material selection. The tool shows potentials for architects to understand the impact of their designs and avoid potential environmental problems.
Simultaneous determination of flouride, iodate and iodide by ion chromatography in caustic off-gas scrubber of nuclear recycle facilities by employing dual detectors

ABSTRACT An ion chromatography method was developed for the simultaneous determination of fluoride, iodate and iodide in a caustic scrubber solution used for trapping off-gases released during the dissolution of nuclear fuels. A separation between iodate and fluoride could be realized with 0.6 mM hydroxide, which is too weak to elute other anions including iodide in reasonable time. Studies were carried out at different column temperature, and with the help of Van’t Hoff plots the thermodynamic parameters associated with the column equilibrium were estimated, which helped in understanding the co-elution of iodate and fluoride at higher concentration of eluent. An arrangement of conductivity detector and UV-VIS detector in sequence after the ion exchange column (with 15 mM NaOH as eluent) was used for recording chromatograms for conductivity signal and UV-VIS signal simultaneously. The information from the two chromatograms was utilized to quantify iodate, fluoride and iodide in a single run. The limit of detection for fluoride, iodate and iodide is 7 ppb, 10 ppb and 12 ppb, respectively. The precision of the method is better than 2% (RSD) at 0.5 mg/L. The method was used successfully for the real sample analysis.
Enhanced Hybrid Converter Topology for PV-Grid-EV Integration

Due to the continuous price reductions in PV modules and significant development in electric vehicles (EV), the integration of solar photovoltaic (PV) into the EV charging system has been inevitable. This paper proposes the control of a hybrid converter in a EV charging station. This system consists of a PV fed Enhanced Hybrid Converter (EHC) integrated with a single-phase grid. The control of the EHC to perceive maximum power from PV, dc voltage regulation for EV charging and AC power control for feeding the AC grid is presented. A testbed under different circumstances i.e., AC and DC power distribution from the solar PV under different insolation conditions, feeding PV power to grid under the absence of EV, feeding PV power to EV charging port in the absence of grid and feeding EV power to grid under the absence of PV power is developed under MATLAB/Simulink environment for validation. Also, a switching logic is proposed for the operation of the EHC converter under no-load condition. The hardware prototype is developed with TI F28379D processor in the laboratory has validated the proposed EHC on various conditions.