Miracle-dz/UniFAR-FTUs huggingface dataset:
Bulletin of Electrical Engineering and Informatics

Received Sep 16, 2022 Revised Dec 16, 2022 Accepted Jan 9, 2023 A significant amount of data is gathered by the healthcare sector, but it is not appropriately mined and utilized. Finding these hidden links and patterns is frequently underutilized. Our study focuses on this element of medical diagnostics by identifying patterns in the information gathered about kidney illness, liver disease, and chronic pancreatitis (CP) and designing adaptive medical decision support systems (MDSS) to assist doctors. This research compares a variety of data mining (DM) techniques, knowledge extraction tools, and software platforms for usage in a DSS for analysis using the Waikato environment for knowledge analysis (WEKA) mining tool (decision tree (DT)). The objective is to determine the most significant risk factors based on the extraction of the categorization criteria. The datasets used for this work are illustrates how successfully DM and DSS are integrated. In this research, we suggest using the C4.5 DT algorithm, Naïve Bayes (NB) algorithm, and the logistic regression (LR) algorithm to categorize these diseases and evaluate their performance and accuracy rates. It inferred that the C4.5 algorithm accuracy is 0.873% which is better than the other two algorithms in terms of rule generation and accuracy.
Shrieking in the face of vengeance

Paraconsistent dialetheism is the view that some contradictions are true and that the inference rule ex falso quod libet (a.k.a. explosion) is invalid. A long-standing problem for paraconsistent dialetheism is that it has difficulty making sense of situations where people use locutions like ‘just true’ and ‘just false’. Jc Beall recently advocated a general strategy, which he terms shrieking, for solving this problem and thereby strengthening the case for paraconsistent dialetheism. However, Beall’s strategy fails, and seeing why it fails brings into greater focus just how daunting the just-true problem is for the dialetheist.
1.2-kV Low-Barrier 4H-SiC JBS Diodes by Virtue of P-Implants Across Dead Field of Current Flow

A low value of Schottky barrier height (SBH) (<inline-formula> <tex-math notation="LaTeX">$\Phi _{B}{)}$ </tex-math></inline-formula> is highly desired to further reduce the power loss in 4H-SiC junction barrier Schottky (JBS) diodes; however, the reduced <inline-formula> <tex-math notation="LaTeX">$\Phi _{B}$ </tex-math></inline-formula> results in serious leakage current (<inline-formula> <tex-math notation="LaTeX">${I}_{R}{)}$ </tex-math></inline-formula> when blocking high voltages. In this work, a tunable low <inline-formula> <tex-math notation="LaTeX">$\Phi _{B}$ </tex-math></inline-formula> of 0.92–0.98 eV with an ideal factor <inline-formula> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> = 1.02–1.03 was first realized through effectual rapid thermal annealing (RTA) methods and combined with a trench-assisted stage-style p-type implants taking advantage of dead region for current flow to resolve the <inline-formula> <tex-math notation="LaTeX">${I}_{\text {R}}$ </tex-math></inline-formula> issue. Numerical simulation demonstrated the superiority of this promising strategy in alleviating the Schottky interface electric field (<inline-formula> <tex-math notation="LaTeX">${E}_{\text {S}}{)}$ </tex-math></inline-formula> and suppressing <inline-formula> <tex-math notation="LaTeX">${I}_{R}$ </tex-math></inline-formula> without constraining the forward current flow. Based on this practical strategy, the fabricated device achieved one order of magnitude less <inline-formula> <tex-math notation="LaTeX">${I}_{R}$ </tex-math></inline-formula> at 25 °C and 220% enhancement of breakdown voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{B}{)}$ </tex-math></inline-formula> at 175 °C in contrast to the conventional low-barrier one. In addition, benefiting from the low <inline-formula> <tex-math notation="LaTeX">$\Phi _{B}$ </tex-math></inline-formula>, the device achieved an ultralow turn-on voltage of 0.47 eV and a remarkable forward voltage drop (<inline-formula> <tex-math notation="LaTeX">${V}_{F}{)}$ </tex-math></inline-formula> of 1.36 V extracted at 20 A, indicating 14% lower conduction loss than the titanium-based JBS diodes with the same device configuration. This novel device structure incorporating low-barrier Schottky contact metal and trench-assisted stage-style p-implants (SPs) in the dead region of current flow suggests a promising way to develop more advanced 4H-SiC JBS diodes in the future.
Event-Triggered Bipartite Consensus of Single-Integrator Multi-Agent Systems with Measurement Noise

Event-triggered bipartite consensus of single-integrator multi-agent systems is investigated in the presence of measurement noise. A time-varying gain function is proposed in the event-triggered bipartite consensus protocol to reduce the negative effects of the noise corrupted information processed by the agents. Using the state transition matrix, Ito^ formula, and the algebraic graph theory, necessary and sufficient conditions are given for the proposed protocol to yield mean square bipartite consensus. We find that the weakest communication requirement to ensure the mean square bipartite consensus under event-triggered protocol is that the signed digraph is structurally balanced and contains a spanning tree. Numerical examples validated the theoretical findings where the system shows no Zeno behavior.
Influence of ion outflow in coupled geospace simulations: 2. Sawtooth oscillations driven by physics‐based ion outflow

We present the first simulations of magnetospheric sawtooth oscillations under steady solar wind conditions that are driven internally by heavy ion outflow from a physics‐based model. The simulations presented use the multifluid Lyon‐Fedder‐Mobarry magnetohydrodynamics model two‐way coupled to the ionosphere/polar wind model (IPWM). Depending on the type of wave‐particle interactions utilized within IPWM, the coupled simulations exhibit either sawtooth oscillations or steady magnetospheric convection. Contrasting the simulations that do and do not develop sawtooth oscillations yields insights into the relationship between outflow and sawtooth oscillations. The total outflow rate is not an adequate predictor of the convection mode that will emerge. The simulations that develop sawtooth oscillations are characterized by intense outflow concentrated in the midnight auroral region. This outflow distribution mass loads the tail reconnection region without excessively mass loading the dayside reconnection region and leads to an imbalance between the dayside and nightside reconnection rates.
Social Influence Maximization in Hypergraph in Social Networks

Crowd psychology plays an important role in determining the kind of activities that a person performs. In reality, in a social network, crowd influence has been observed and it cannot be ignored when considering information diffusion problems. In this paper, we model crowd influence as a hyperedge <inline-formula><tex-math notation="LaTeX">$e=(H_e,v)$</tex-math></inline-formula> with weight <inline-formula><tex-math notation="LaTeX">$0\leq P_e\leq 1$</tex-math></inline-formula>, where <inline-formula><tex-math notation="LaTeX">$H_e$</tex-math></inline-formula> is the head node set and <inline-formula><tex-math notation="LaTeX">$v$</tex-math></inline-formula> is the tail node, means <inline-formula><tex-math notation="LaTeX">$v$</tex-math></inline-formula> will be activated by <inline-formula><tex-math notation="LaTeX">$H_e$</tex-math></inline-formula> with probability <inline-formula><tex-math notation="LaTeX">$P_e$</tex-math></inline-formula> only after each node in <inline-formula><tex-math notation="LaTeX">$H_e$</tex-math></inline-formula> is activated. Then, the Social Influence Maximization Problem in Hypergraph (SIMPH) aims to select <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> initially-influenced seed users in a directed hypergraph <inline-formula><tex-math notation="LaTeX">$G=(V,E,P)$</tex-math></inline-formula>. The objective is to maximize the expected number of eventually-influenced users. We show that SIMPH is NP-hard and the objective function is neither submodular nor supermodular. We develop a lower bound and an upper bound that are submodular. We prove that maximizing these two bounds are still NP-hard under IC model. Then, we present a D-SSA algorithm for general weighted social influence maximization problem preserving <inline-formula><tex-math notation="LaTeX">$(1-1/e-\epsilon)$</tex-math></inline-formula>-approximation. We formulate a sandwich approximation framework, which preserves a theoretical analysis result. Finally, we evaluate our algorithm on real world data sets. The results show the effectiveness and the efficiency of the proposed algorithm.
Connecting Microstructures for Multiscale Topology Optimization With Connectivity Index Constraints

With the rapid developments of advanced manufacturing and its ability to manufacture microscale features, architected materials are receiving ever increasing attention in many physics fields. Such a design problem can be treated in topology optimization as architected material with repeated unit cells using the homogenization theory with the periodic boundary condition. When multiple architected materials with spatial variations in a structure are considered, a challenge arises in topological solutions, which may not be connected between adjacent material architecture. This paper introduces a new measure, connectivity index (CI), to quantify the topological connectivity, and adds it as a constraint in multiscale topology optimization to achieve connected architected materials. Numerical investigations reveal that the additional constraints lead to microstructural topologies, which are well connected and do not substantially compromise their optimalities.
HOUSEHOLD FOOD AND NON-FOOD CONSUMPTION BEHAVIOUR IN PAKISTAN

The main objective of the study is to identify the household consumption pattern in Pakistan. To fulfill the objective, the research incorporates microdata of household expenditure on twenty food and nonfood groups for the period 2018- 19. Different socioeconomic and demographic variables are also used to explain household consumption behaviour. It is concluded that most of the expenditure share of food and non-food groups of commodities has increased due to an increase in per capita income, but at a decreasing rate. Household size, household age and employment by age and by gender have played a significant role in altering the consumption share of most of food and nonfood commodities. There are both provincial and regional disparities exist in consumption behavior. Housing is considered a normal or luxurious good, while education is inferior because the expenditure share of housing has increased as income has increased, and so on. It is suggested that the government should work to increase the awareness regarding the importance of education.
Mesoscale Disturbances and Related Rainfall Cells Embedded in the "Baiu Front", with a Proposal on the Role of Convective Momentum Transfer

The frequency distribution of the wave length of mesoscale disturbances is studied for a 3-day period from July 8 to July 11, 1968, when an active "Baiu front" was situated over the Kyushu district. The predominant wave length of mesoscale disturbances is shown to be about 150~200 km. A series of mesoscale disturbances accompanied by heavy precipitation are studied in detail particularly for the case of July 9. Significant rainfall amounts were limited to the southern part of Kyushu where a low-level jet stream was located, while the configuration of the associated mesoscale pressure system was elongated in the north-south direction to a large extent. Stages of precipitation intensity depend on the spatial phase relationship between the pressure and the divergence fields. The synoptic-scale divergence and vorticity of the surface wind are found to fluctuate with a very short period of the order of 1.5~3 hours. The phase difference between the fluctuation of divergence and that of vorticity changes from "in phase" to gout of phase" when a cyclone passes over Kyushu. This seems to be due to the convective exchange process in the area of convergence.
Development of novel textile and yarn actuators using plasticized PVC gel

Soft actuators based on polymers are expected to be used for power sources to drive wearable robots which required in a wide range of fields such as medical, care and welfare, because they are light weight, flexible and quiet. Plasticized PVC gel which has a large deformation by applying a voltage and high driving stability in the atmosphere is considered as a suitable candidate material for development of soft actuator. Then, we proposed two kinds of novel flexible actuators constructed like yarn and textile by using plasticized PVC gel to develop soft actuator to realize a higher flexibility and low-voltage driving. In this study, we prepared prototypes of these actuators and clarify their characteristic. In addition, we considered the deformation model from its characteristics and geometric calculation. When a voltage was applied to their actuators, textile type actuator was contracted, while the twisted yarn type actuator was expanded. The deformation behavior of the proposed actuators could be found at a low voltage of 200V, the contraction strain of the textile actuator was about 27 %, and the expanding ratio of the yarn actuator was 0.4 %. Maximum contraction strain of textile actuator and expansion ratio of yarn actuator was 53% and 1.4% at 600 V, respectively. The calculation results from the proposed model were in roughly agreement with the experimental values. It indicated that deformation behavior of these actuators could estimate from models.
Dense Fluid Flow Estimation

In this paper we address the problem of estimating and analyzing the motion in image sequences showing fluid phenomenon. Due to the great deal of spatial and temporal distortions that luminance patterns exhibit in images of fluid, standard techniques from Computer Vision, originally designed for quasi-rigid motions with stable salient features, are not well adapted in this context. In that prospect, we investigate a dedicated energy-based motion estimator. The considered functional includes an original data model relying on the continuity equation of fluid mechanics. This new data model, which is specifically designed to be embedded in a multiresolution framework, is associated to an original div-curl type regularization. The optimization of the global energy function is solved within an efficient multigrid scheme. The performances of the resulting fluid flow estimator are demonstrated both on synthetic and real (meteorological) image sequences.
A new hybrid recursive regularised Bhatnagar–Gross–Krook collision model for Lattice Boltzmann method-based large eddy simulation

ABSTRACT A new Lattice Boltzmann collision model for large eddy simulation (LES) of weakly compressible flows is proposed. This model, referred to as the Hybrid Recursive Regularised Bhatnagar–Gross–Krook (HRR-BGK) model, is based on a modification of previously existing regularised collision models defined with the BGK Lattice Boltzmann method (LBM) framework. By hybridising the computation of the velocity gradient with an adequate Finite Difference scheme when reconstructing the non-equilibrium parts of the distribution function, a hyperviscosity term is introduced in the momentum equation, whose amplitude can be explicitly tuned via a weighting parameter. A dynamic version of the HRR-BGK is also proposed, in which the control parameter is tuned at each grid point and each time step in order to recover an arbitrarily fixed total dissipation. This new collision model is assessed for both explicit and implicit LES considering the flow around a circular cylinder at . The dynamic HRR-BGK is observed to yield very accurate results when equipped with Vreman's subgrid model to compute the target dissipation.
LASSO tuning parameter selection

The LASSO is a penalized regression method which simultaneously performs shrinkage and variable selection. The output produced by the LASSO consists of a piecewise linear solution path, starting with the null model and ending with the full least squares fit, as the value of a tuning parameter is decreased. The performance of the selected model therefore depends greatly on the choice of this parameter. This paper attempts to provide an overview of methods which are available to select the value of the tuning parameter for either prediction or variable selection purposes. A simulation study provides a comparison of these methods and assesses their performance.
Sliding innovation filter for micorgrid application

Currently, microgrids are frequently used and various control algorithms have been applied to improve their performance in both grid-connected and islanded modes. However, research has shown that incorporating a filtering technique into the controller can lead to even better performance. As a result, a simple controller with a filter can perform just as well as a complex controller that operates alone. This study focuses on the performance of a microgrid using a new filter called the sliding innovation filter, which is known for its robustness and stability. The filter is an excellent option for estimating performance under various conditions, such as load and injected powers. To demonstrate the filter's advantages, modeling uncertainties are introduced into the system while the filter is estimating states. The filter's performance is evaluated using a MATLAB© simulation environment.
How Hungarian teachers think about combinatorics and its teaching

Teachers’ attitudes and beliefs have a fundamental influence on the way of teaching and the efficiency of learning. This topic was also brought up in the didactic research in recent years, in connection with mathematics teachers as well. – To the best of our knowledge, however, a study that investigates this specific area (combinatorics) was not included. As combinatorics has a special role in connecting the development of mathematical thinking and teaching different areas, our short-time Project (Didactics Grant of the Hungarian Academy: Complex Mathematics Education in the 21st Century) focused on the teaching of combinatorics in Hungary. Our aim was to examine some aspects of this field in connection with Tamás Varga’s method and also teachers’ beliefs towards combinatorics with the help of a questionnaire. The main results of this survey are discussed below.
Regional curve standardization of visually classified tree-ring features

Time-series of the relative frequency of visually classified tree-ring features are meanwhile an established method to estimate the climatic background of latewood density anomalies like e.g. intra-annual density fluctuations (IADFs). IADFs are a direct reaction of trees to specific patterns of environmental conditions (e.g. Wimmer et al. 2000). In the Mediterranean region, drought stress in summer can initialize cell-wall thickening and trigger the formation of terminal cell rows. Precipitation following such a drought phase with cambial dormancy can reactivate cell formation and thus lead to the formaton of an IADF (e.g. Campelo et al. 2007). The relative frequency of other distinct ring-types such as narrow, missing, or light rings can also be used as indicator of specific environmental conditions. Since the first analyses of the relative frequency of visually classified tree-ring features, there have been discussions about the effects of age-trends inherent in frequency time-series. Some studies observed a decrease of IADFs towards cambially older rings (Brauning 1999, Wimmer et al. 2000, Copenheaver et al. 2006). To address this problem, one possible solution is the use of age-classes in order to assess the age-dependency of the frequency (Vieira et al. 2009). A second method selects relatively old-grown trees to minimize age-related effects (Wimmer et al. 2000, Vieira et al. 2010). However, none of these methods can effectively remove age-related artefacts in time-series of relative frequencies. In ring-width studies, cubic smoothing splines are often applied to each single series to remove age-trends and non-climatic disturbances (Cook 1981). However, long-term climatic signals are likely to be removed from the resulting standardized index series. Hence, regional curve standardization (RCS) is increasingly applied to retain low frequency signals and to effectively remove age-related biases (for a review see Esper et al. 2003, Briffa & Melvin 2011). In contrast to ring-width series, splining of single IADF curves is not possible due to the binary nature of the IADFs. Applying spline-detrending to curves of a relative frequency will result in a loss of any trend in the signal. Another important issue in ring-width analysis is the quality assessment of chronologies. Different parameters were developed to assess the signal strength or the confidence of a chronology, such as the mean correlation between all series forming a chronology ( r or rbar) (Briffa & Jones 1990) and the expressed population signal (EPS; Wigley et al. 1984). EPS estimates how well the signal of the sample collection reflects a theoretical chronology which consists of an infinite number of samples. EPS uses the mean sample number of a given interval and the mean (Pearson’s) correlation between the samples for a maximum common overlap period:
Cosine Kuramoto Based Distribution of a Convoy with Limit-Cycle Obstacle Avoidance Through the Use of Simulated Agents

Cosine Kuramoto Based Distribution of a Convoy with Limit-Cycle Obstacle Avoidance Through the Use of Simulated Agents William Howerton Chair of the Supervisory Committee: Professor Mehran Mesbai William E. Boeing Department of Aeronautics and Astronautics This thesis presents a method for the integration of complex network control algorithms with localized agent specific algorithms for maneuvering and obstacle avoidance. This method allows for successful implementation of group and agent specific behaviors. It has proven to be robust and will work for a variety of vehicle platforms. Initially, a review and implementation of two specific algorithms will be detailed. The first, a modified Kuramoto model was developed by Xu [1] which utilizes tools from graph theory to efficiently perform the task of distributing agents. The second algorithm developed by Kim [2] is an effective method for wheeled robots to avoid local obstacles using a limit-cycle navigation method. The results of implementing these methods on a test-bed of wheeled robots will be presented. Control issues related to outside disturbances not anticipated in the original theory are then discussed. A novel method of using simulated agents to separate the task of distributing agents from agent specific velocity and heading commands has been developed and implemented to address these issues. This new method can be used to combine various behaviors and is not limited to a specific control algorithm.