Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear Discriminant Analysis Cauchy Estimator for Single Chinese Character Font Recognition

In machine learning area, the rapid development of optical character recognition (OCR) has prompted interest in Chinese character font recognition (CCFR), especially single Chinese character font recognition. However, when pre-processing pollutes Chinese font images with noise, traditional font recognition algorithms tend not to be suitably discriminant. In this paper, and based on linear discriminant analysis and Cauchy estimator theory, we propose a novel feature selection algorithm called linear discriminant analysis Cauchy estimator (LDACE) for single Chinese character font recognition. LDACE aims to: (1) consider both between-class and within-class geometry in the low-dimensional space, and (2) preserve recognition when input samples are polluted with noise. Experiments with the frequently used FUCCFR dataset demonstrate LDACE’s effectiveness.
Type-II Fuzzy Multi-Product, Multi-Level, Multi-Period Location–Allocation, Production–Distribution Problem in Supply Chains: Modelling and Optimisation Approach

ABSTRACT In this study, the application of type-II fuzzy sets is addressed to design a multi-product, multi-level, multi-period supply chain networks. The proposed model provides integrated approach to make optimal decisions such as location–allocation, production, procurement and distribution subject to operational and tactical constraints. In the context of fuzzy linear programming, this study involves type-II fuzzy numbers for the right-hand side of constraints regarding three sources of uncertainty: demand, manufacturing and supply. According to fuzzy components considered, a type-II fuzzy mixed-integer linear programming is converted into an equivalent auxiliary crisp model using linear fuzzy type-reducer models. The final models are linear and the global optimum solutions can be achieved using commercial OR softwares. The contributions of this study are three folds: (1) introducing a new integrated supply chain network design problem; (2) considering a solution procedure based on type-II fuzzy sets and (3) presenting a linear fuzzy type-II reducer. Finally, the proposed model and solution approach are illustrated through a numerical example to demonstrate the significance.
The Application of Constructive Alignment Theory in Designing a Curriculum Unit in Information Systems

The outcomes based approaches to learning have been shown to have a significant impact on student success in higher-order learning. Constructive alignment is an outcomes-based approach to teaching in which the learning outcomes that students are intended to achieve are defined before teaching takes place. Teaching and assessment methods are then designed to best achieve those outcomes and to assess the standard at which they have been achieved. It provides a framework for adjusting teaching and assessment to address the attainment of those outcomes and the standards reached. Constructive alignment is effective in designing teaching and assessment that enable students to learn, rather than to leave them guessing as to what is involved in the course of study or on what they will be assessed. The paper highlights the importance of using constructive alignment framework to enhance the quality of teaching, learning, and assessment. It reports on a study that applied the principles of constructive alignment to promote good teaching and deep student learning. It discusses the application of constructive alignment as curriculum design process and uses operational framework for this teaching design at the unit level.
Does Maintained Medical Aid Coverage Affect Healthy Lifestyle Factors, Metabolic Syndrome-Related Health Status, and Individuals’ Use of Healthcare Services?

Concerns about the moral hazards and usage of universal health insurance require examination. This study aimed to analyze changes in lifestyle, metabolic syndrome-related health status, and individuals’ tendency to use healthcare services according to changes in the eligibility status of medical aid recipients. This paper reports a retrospective cohort study that involved analyzing data from 2366 medical aid recipients aged 40 years or older who underwent national health screenings in 2012 and 2014. Of the recipients, 1606 participants continued to be eligible for medical aid (the “maintained” group) and 760 changed from being medical aid recipients to National Health Insurance (NHI) enrollees (the “changed” group). Compared to the “changed” group, the “maintained” group was less likely to quit smoking, more likely to begin smoking, less likely to reduce binge drinking to moderate drinking, and had a significant increase in blood glucose and waist circumference. Annual total medical expenses also increased significantly in the “maintained” group. Since the mere strengthening of healthcare coverage may lead to moral hazards and the failure to link individuals’ tendency to use healthcare services and outcomes, establishing mechanisms is necessary to educate people about the health-related outcomes of maintaining a healthy lifestyle and ensure the appropriate use of healthcare services.
Comet C/2013 V5 (Oukaimeden): Evidence for Depleted Organic Volatiles and Compositional Heterogeneity as Revealed through Infrared Spectroscopy

We obtained high-resolution (λ/Δλ ∼ 25,000) pre-perihelion spectra of Comet C/2013 V5 (Oukaimeden) using NIRSPEC at Keck II on UT 2014 September 5–6, and CSHELL at the NASA-Infrared Telescope Facility on September 11–13, altogether spanning a range in heliocentric distance Rh = 0.789–0.698 au. We report water production rates, and production rates and abundance ratios relative to co-measured H2O for eight trace molecules: CO, H2CO, CH3OH, CH4, C2H2, C2H6, HCN, and NH3. Our measured water production rates from NIRSPEC and CSHELL observations remained relatively constant and were close to those from SOHO/Solar Wind ANisotropies observations that encompassed our dates, suggesting H2O production dominated by release directly from or within approximately 2000 km of the nucleus. All trace volatiles were depleted relative to their respective median abundances among comets, excepting NH3, which was consistent with its median abundance. Most surprising were pronounced increases in abundance ratios for CH3OH (by 51% relative to simultaneously measured H2O) and especially C2H6 (by 87%) between September 5 and 6. On September 5, C2H6 was severely depleted, consistent with its lowest abundance yet measured for any comet. It also tracked the spatial profile of H2O, suggesting C2H6 was associated with a polar ice phase dominating gas production. On September 6, C2H6 was only moderately depleted and was spatially distinct from H2O, suggesting both polar- and nonpolar-dominated ice phases contributed to the activity then. Our results are consistent with a nonhomogeneous volatile composition for C/2013 V5, implying differential processing of its constituent ices.
On the basis properties of the functions arising in the boundary control problem of a string with a variable tension

We consider the boundary control problem for a string. We say that the string is controllable if, by suitable manipulation of the exterior force, the string goes to rest. To prove our controllability results we apply the method of characteristics. Then, using the method of moments we establish a connection between the boundary control problem and the basis property of a system of functions that substitutes the system of nonharmonic exponential functions. The latter system regularly appears in the problems of controllability since the classical papers of H.O. Fattorini and D.L. Russell.
Optical design considerations and raytracing results for the Arcus grating spectrometer concept

Arcus is a mission concept for a next generation X-ray grating spectrometer. It will offer spectral resolution (λ/▵λ) greater than 2000 combined with over 500 cm2 of effective area in the 2.1-2.4 nm bandpass. These capabilities will elucidate the cycle of baryonic matter in and out of galaxies, the means by which supermassive black holes influence their surroundings, and the early formation and evolution of solar systems. We present the overall optical design of the mission, which features four arrays of silicon pore optics modules with four matching arrays of off-plane reflection grating modules. These optics disperse the incident X-rays over the 12 m focal length in four separate conical diffraction patterns onto CCD arrays at the focal plane. Each array of optics is an azimuthal sub-aperture of the typical Wolter telescope design, enabling enhanced spectral resolution due to an asymmetric point spread function. The theoretical spectral resolution, effective area, and alignment tolerances have been determined via raytrace modeling.
A Low Cross-Polarization Microstrip Antenna Array for Millimeter Wave Applications

A low cross-polarization microstrip antenna array for millimeter wave (mmW) applications is proposed in this paper. The antenna element is composed of symmetric T-shaped patches with vias. The adoption of a double-sided symmetric radiation patch structure can suppress the cross-polarized electric field, and the vias reduces energy leakage during the power transmission along the antenna patches. To verify the concept, a 1 × 8 antenna array is fabricated and measured. The measured −10 dB impedance of the antenna array is 28.4% (31 GHz–41.5 GHz) and the peak gain is 15 dBi. The cross polarization ratio is above 35 dB and the 3 dB beamwidths on E-plane and H-plane are 7.5° and 135°, respectively. The proposed compact size and low cross-polarization antenna array might be a good choice for phased array radar and 5th generation (5G) mobile communication applications.
Sustainability and urban climate: How Metaverse can influence urban planning?

Metaverse is a unique space in a virtual world that with many capabilities and features shows us a world in which we can experience life in all its dimensions. The presence of Metaverse in the global arena and the use of the facilities of this technology are effective in improving living conditions in developing cities. In this study, two sample projects that Metaverse can support are presented in India and Ghana. The remarkable thing is its innovative method that can solve many problems in the cities of the world. One of the most important challenges in the world today is saving cities from climate change and its adverse effects. Metaverse is one of the innovative methods to reduce the effects of greenhouse gas emissions in the cities of the world. The question is whether Metaverse can influence the urban planning of many cities in the world and change urban planning in the world internationally? And can Metaverse challenge the theoretical foundations in the city? The purpose of this study is to clarify the effects of the Metaverse on the city level. This study aims to introduce a new way to solve the problems of today and the future of world cities by examining Upland and its effects on urban sustainability and ways to prevent climate change. In this context, Metaverse technology has been used as a new solution to provide jobs, reduce poverty, increase public health, prevent climate change and, as a result, realize a better life for future generations. The results of this study, due to being cross-border and creating a global perspective on the Metaverse in urban planning, can create a new scientific perspective based on technological advances in urban studies.
Delay-dependent robust H∞ control for uncertain systems with time-varying delays

The paper deals with the robust H∞ control problem for uncertain linear systems with multiple state delays. The parameter uncertainties are time varying and unknown, but are norm-bounded, and the delays are time varying. Based on the LMI approach, a new method for designing a robust memoryless state feedback control law is proposed to stabilise this class of uncertain time-delay systems, and to reduce the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. The results depend on the size and the varying rate of the delays and may be less conservative.
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like identifying the sequence of events in the Laparoscopic Cholecystectomy (LC). This study will contribute to show the effectiveness of CNN-CLM approach on laparoscopic cholecystectomy, which will frequently focus on surgical computer vision analysis of surgical safety and related applications. The method of study is deep learning based CNN-CLM to better detect nominal safety as well as unsafe practices around the critical view of safety and AI-based grading scale. The general design flow of AI-recognition of surgical safety is firstly collecting safety surgical videos for frame segmenting and phase according to the image context by surgeon reviewer by CNN-CLM. For this advance research, the dataset is splatted into three main parts where 70% of which is used for training, 15% of which is used for testing and the rest for the cross validation, to achieve the accuracy up to 98.79% of this specific research. For result part, different metrics of CNN-CLM to evaluate the performance of the proposed model of safety in surgery. The study uses one of the top three performing methods CNN-CLM for the evaluation yields and anatomical structures in laparoscopic cholecystectomy surgery.
Caracterização do Backlog e do Atraso em Servidores GPS Sob Tráfego Auto-Similar

Neste artigo é apresentado um algoritmo para a obtenção de valores limitantes para o backloge para o atraso introduzido no tráfego de fontes auto-similares por um servidor que utiliza como disciplina de serviço o Generalized Processor Sharing. Este trabalho é uma extensão do estudo desenvolvido por Parekh e Gallager [9], que obtêm limitantes para fontes de tráfego reguladas pelo algoritmo do Balde Furado. Por outro lado, o presente trabalho considera que tráfego das fontes é regulado pelo algoritmo do Balde Furado Fractal proposto por Viana Neto [2] e desta forma pode ser modelado pelo processo envelope do movimento Browniano fracionário, que considera a efetiva natureza auto-similar do tráfego nas redes de serviços integrados.
GARAPENAREN EREDU TEORIKOAK

Giza garapenean bere testuinguru fisiko eta sozialaren alderdi ezberdinek eragina dute. Hala ere, gizabanakoak ingurunearekiko sentsibilitatean eta honi erantzuteko gaitasunean desberdinak dira, batzuk ingurune-baldintza berberen aurrean sentiberagoak izanik [1]. Tradizioz, desberdintasun indibidual hauek diatesi-estresaren [4, 5] eredutik aztertu izan dira. Honen arabera, pertsona batzuk, beren zaurgarritasun ezaugarri endogenoengatik, neurrigabeko zaurgarriak dira esperientzia negatiboen edo ondorio kaltegarrien aurrean, zaurgarritasun txikiagoko banakoekin alderatzean. Ikuspegi ebolutiboari jarraikiz, badaude beste bi eredu teoriko, sentikortasun diferentzialaren eredua [18, 22] eta testuinguruarekiko sentsibilitate biologikoaren eredua [16], zeinak gizabanako batzuk sentikortasunaren ezaugarri indibidualengatik ingurumen-eragin negatibo zein positiboen aurrean neurrigabeago jasaten dituztela dioten. Hortaz, ingurune positiboetatik onura gehiago lortuz, eta, aldi berean, ingurune negatiboekiko zaurgarriagoak izanik. Azkenik, badago beste teoria berriago bat, sentsibilitate abantailatsuaren eredua [11], zeinak gizabanako batzuk, beren sentikortasun faktoreengatik, ingurumen-abantailei edo testuinguru positiboei sentikorragoak direla eta positiboki erantzuten dutela proposatzen duena, banako hauek ahalmen hori ez dutenen aldean abantaila bat aurkeztuz.
Small Size Broadband Printed Antenna for 5G Applications Covering 28 GHz / 38 GHz and 60 GHz Bands

This work offers the radiation insight of a compact modified monopole rectangular printed antenna suitable for 5G applications. A Double copper cladded RT Duroid 5880 material sheet with dimensions 4.4×5.0×0.5mm3 is chosen as the base substrate in the offered design with a loss tangent of 0.004 and a dielectric constant of 2.2. In the provided strategy lower-left corner of a rectangular printed antenna is made in the form of a smooth circular curve. After extensive simulation, a circular slot with an elliptical patch is incorporated into this monopole antenna. The designed antenna parameters are adjusted to cover the impedance bandwidth from 21.7 GHz to more than 70.0 GHz. Three resonances at 28.0 GHz, 38.1 GHz and 60.2 GHz were observed in three bands allocated for 5G communication applications. The efficiency and gain values found sustained in the entire bandwidth range. Stable and desired radiation patterns at all three resonant frequencies 28/38/60 GHz prove the suitability of this antenna for recent 5G applications.
Sampling from the 𝒢 I 0 distribution

Abstract Synthetic Aperture Radar (SAR) images are widely used in several environmental applications because they provide information which cannot be obtained with other sensors. The 𝒢 I 0 {\mathcal{G}_{I}^{0}} distribution is an important model for these images because of its flexibility (it provides a suitable way for modeling areas with different degrees of texture, reflectivity and signal-to-noise ratio) and tractability (it is closely related to the Snedekor-F, Pareto Type II, and Gamma distributions). Simulated data are important for devising tools for SAR image processing, analysis and interpretation, among other applications. We compare four ways for sampling data that follow the 𝒢 I 0 {\mathcal{G}_{I}^{0}} distribution, using several criteria for assessing the quality of the generated data and the consumed processing time. The experiments are performed running codes in four different programming languages. The experimental results indicate that although there is no overall best method in all the considered programming languages, it is possible to make specific recommendations for each one.
Model‐based architecting evaluation method for the delivery of complex nuclear projects

Facing the organizational and technological complexity of nuclear infrastructures (NI), the public reluctance in nuclear technology and the increasing restrictive regulatory environment, improving the conceptualization and evaluation of NI architecture is crucial for the successful completion of NI projects. Indeed, many technical engineering difficulties or delays in delivery can be avoided by deepening the design and evaluation of NI architectures. In a context where model‐based systems engineering (MBSE) is becoming more and more relevant, it is interesting to integrate evaluation into this process. Although the architecture evaluation (AE) process is rather well defined in the literature and linked to system analysis practices, it is quite difficult to deploy and pilot within complex NI projects. This article proposes a model‐based method, EVAluation for Critical Infrastructure Model Based System Engineering (EVA‐CIME), to facilitate the deployment of AE processes on a project. The components of this method are described and illustrated in a study of a NI design. The benefits and limitations of EVA‐CIME in its state of development are discussed and lead to the conclusion that the method should be extended to foster an AE culture within the company itself.
Relationship of Cyberbullying and Mental Health in Malaysian Society

Due to the negative psychosocial repercussions as well as the challenges brought on by irresponsible use of technology, researchers and society have increased their attention on cyberbullying. In relation to this, online media has been reported to be linked with cyberbullying and mental health, nevertheless, the links remain unclear. Thus, this present study aimed to contribute to providing a framework that predicts cyberbullying factors that lead to mental health issues. Using the convenience sampling method, 154 questionnaires were collected from Malaysian respondents as part of the study's quantitative research approach. The data were analyzed through the Structured Equation Modeling (SEM) technique using Smart PLS version 3.2. 8 to investigate the predictive capacity of cyberbullying antecedents (Cyberbullying Experience, Self-Esteem, and Social Connectedness) towards cyberbullying experience. The findings demonstrated a strong correlation between cyberbullying and an increase in mental health issues in Malaysian society. The study also confirmed that there is a strong link between social contagion theory and cyberbullying. The importance of this research will raise Malaysians' awareness by encouraging moral behavior when using social media and policing instances of cyberbullying.
Sparse Modeling of Harmonic Signals

This thesis considers sparse modeling and estimation of multi-pitch signals, i.e., signals whose frequency content can be described by superpositions of harmonic, or close-to-harmonic, structures, characterized by a set of fundamental frequencies. As the number of fundamental frequencies in a given signal is in general unknown, this thesis casts the estimation as a sparse reconstruction problem, i.e., estimates of the fundamental frequencies are produced by finding a sparse representation of the signal in a dictionary containing an over-complete set of pitch atoms. This sparse representation is found by using convex modeling techniques, leading to highly tractable convex optimization problems from whose solutions the estimates of the fundamental frequencies can be deduced.In the first paper of this thesis, a method for multi-pitch estimation for stationary signal frames is proposed. Building on the heuristic of spectrally smooth pitches, the proposed method produces estimates of the fundamental frequencies by minimizing a sequence of penalized least squares criteria, where the penalties adapt to the signal at hand. An efficient algorithm building on the alternating direction method of multipliers is proposed for solving these least squares problems.The second paper considers a time-recursive formulation of the multi-pitch estimation problem, allowing for the exploiting of longer-term correlations of the signal, as well as fundamental frequency estimates with a sample-level time resolution. Also presented is a signal-adaptive dictionary learning scheme, allowing for smooth tracking of frequency modulated signals.In the third paper of this thesis, robustness to deviations from the harmonic model in the form of inharmonicity is considered. The paper proposes a method for estimating the fundamental frequencies by, in the frequency domain, mapping each found spectral line to a set of candidate fundamental frequencies. The optimal mapping is found as the solution to a minimimal transport problem, wherein mappings leading to sparse pitch representations are promoted. The presented formulation is shown to yield robustness to varying degrees of inharmonicity without requiring explicit knowledge of the structure or scope of the inharmonicity.In all three papers, the performance of the proposed methods are evaluated using simulated signals as well as real audio. (Less)