Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of a Hybrid Model Based on ICEEMDAN, Bayesian Hyperparameter Optimization GRU and the ARIMA in Nonferrous Metal Price Prediction

Abstract Nonferrous metals are the basic materials for national economic development. Accurate and robust price forecasting can effectively reduce investment costs and bring greater economic benefits to enterprises. But the violent fluctuation of nonferrous metal prices and the evolution of irregular cycles make metal price prediction difficult. A nonferrous metal price prediction model based on improved complementary ensemble empirical mode (ICEEMDAN) decomposition, a Bayesian hyperparameter optimization gated recurrent neural network (GRU) and an integrated autoregressive moving average model (ARIMA) is proposed. First, ICEEMDAN is used to decompose the original metal price series, and then fuzzy entropy is applied to judge the complexity of confusion of the decomposed subsequence. An ARIMA model is used to predict the sequence with the minimum fuzzy entropy, and the other subsequences are predicted by the Bayesian hyperparametric optimization GRU in this article. Finally, the prediction results are integrated to obtain the final prediction results of the original price series. To verify the reliability and practicability of the model in this article, different lengths of daily futures price series of zinc, aluminum, copper and gold prices on the London Metal Exchange and the Investing are used as the research data, three experiments utilizing 5 groups of metal price data and 10 comparison models are designed to verify the superiority of the proposed model. The results show that: (i) Bayesian hyperparameter optimization can improve the prediction performance of a single model effectively. The hybrid method with fuzzy entropy can effectively improve the prediction accuracy. (ii) The proposed model outperforms the compared state-of-the art models in three-step metal prices forecasting.
Malware Detection From The Network Perspective Using NetFlow Data

V prezentaci bude představen nový botnet Chuck Norris, který jsme objevili koncem roku 2009 za pomoci statistických informaci o siťových tocich. Na zakladě tohoto objevu jsme navrhli a implementovali rozsiřujici modul kolektoru NfSen, který automatizovaně detekuje chovani tohoto botnetu. V prezentaci se take zabývame popisem architektury modulu a konkretnich metod pro detekci chovani botnetu.
Escalaridade e prototipia no domínio da intercalação: o caso das cláusulas hipotáticas circunstanciais temporais no espanhol mexicano oral

Based on the assumptions and principles of Usage-based Theory (Bybee 2010 e Furtado da Cunha et al. 2013), in this article, we analyze the intercalation of Temporal Circumstantial Hypothatic Clauses in data from 54 interviews from the Corpus Sociolingüístico de la Ciudad de Mexico (CSCM), treating it as a category of prototypes. The 514 data reveal 13 types, among which the exemplary Auxiliary verb of periphrasis (∆) Temporal (∆) Main verb of periphrasis was considered the most prototypical case of intercalation of Temporal, based on high structural complexity, low token frequency and low productivity (frequency in type). We also realized that the most typical textualdiscursive function of intercalated clauses is guide/circumstantial orientation. From a cognitive point of view, the uses of intercalated clauses, from the prototype to the margin, are motivated by mechanisms that tend to reduce coding efforts, reflecting iconicity, markedness (Givón 1995, 2001) and expressiveness (Dubois and Votre 2012).
Assessment of Knowledge and Attitude in the Field of Doping in Young Athletes of Team Games

contemporary sport is becoming more and more commercialized, hence the players strive to win at all costs, and to achieve this goal, they consider all means to be allowed. in order to be constantly on top, competitors change their training methods, use various aids, and finally direct their interests towards doping. Doping is considered to be the use of substances and all means intended to artificially increase physical fitness during sports competitions, which may be harmful to the ethics of sport or cause mental and physical harm to athletes. The aim of the research is to assess the knowledge of the problem and attitudes of young people practicing sports games towards the dangers of doping. assessment of knowledge on the effects of the use of illicit means, and analysis of opinion on the use of doping and strengthening mechanisms for the adoption of pharmacological agents. research on the knowledge about the use of support measures and doping in sport was carried out among talented youth practicing team sports games in randomly selected clubs of Małopolska, silesia, Podkarpacie and Opole. continuation studies were conducted in 2018–2020, they covered 60 girls and 60 boys, aged 16 years. The research was carried out using a questionnaire, the questions of which concerned the following problems: knowledge of the essence of sports doping, the relationship between doping and the principle of fair play in sport, support used in physical recreation, reasons for the use of doping, moral and criminal liability in the use of doping. when analyzing the results of the research, it should be noted that the use of doping in sport is negatively perceived by the examined youth. however, it can be assumed that the knowledge about the support and the problem of doping in sport is insufficient. setting the main goal – sports success and the related financial rewards, as well as the willingness to be the best in the opinion of the respondents may narrow the boundaries, which may facilitate the decision to use support and doping. These observations seem to be very disturbing, as the analysis of research data concerns young people practicing sports at the stage of education and the utilitarian nature of physical activity.
L 2-L ∞ state estimation for continuous stochastic delayed neural networks via memory event-triggering strategy

In this paper, we study the memory event-triggering - state estimation for a type of continuous stochastic neural networks (NNs) subject to time-varying delays. The information of some recent released packets is made use in the proposed triggering conditions to schedule the data propagation, thereby reducing communication frequency and saving energy. By taking into account network-induced complexities (i.e. transmission delays and random disturbances), we first formulate the evolutions of estimation error in an augmented form, and then propose the conditions under with the design goals could be met. By using certain novel Lyapunov–Krasovskii (L–K) functionals in combination with stochastic analysis technique, sufficient conditions have been provided for the existence of desired estimator, guaranteeing both the globally asymptotically mean-square stability and the prescribed - performance simultaneously. Moreover, the estimator gains are obtained by virtue of certain convex optimisation algorithms. Finally, we use an illustrative example to verify the obtained theoretical algorithm.
Implementation of Photovoltaic Panel MPPT Through Robust Feedback Linearization Controller

Abstract Because of nonlinear I-V curves of photovoltaic panels, a maximum power point tracking (MPPT) technique is necessary to absorb maximum power. In this article state-space averaging method is utilized to express behavior of boost chopper converter. To generate the best operating point (PV panel desired voltage), incremental conductance is used. A Robust feedback linearization controller is proposed to deliver the PV panel to maximum power point. The controller is robust to environment variations, load uncertainties and load voltage disturbances. Stability of proposed controller is proved based on Lyapunov theorem. A boost chopper is used between PV panel and load to realize proposed MPPT technique. Boost chopper parameters are designed properly to operate converter in continues conduction mode (CCM). To evaluate MPPT technique some simulations in irradiance variation, temperature variation, load variation and load voltage disturbance are presented and discussed.
Beam combination scheme for multi-user massive MIMO systems

Channel state information (CSI) at the base station (BS) is crucial to fully exploit the advantages of massive multiple-input multiple-output (MIMO) systems. In frequency division duplexing systems, CSI is obtained through downlink channel estimation and uplink CSI feedback. The conventional CSI acquisition scheme, which has been designed based on the beam selection principle, suffers from severe multi-user interference when same beamforming vector is selected for different user equipments (UEs), and the spatial richness of the channel cannot be captured by the selected beamforming vector for the rich scattering environment. To address such issues, a beam combination scheme is proposed by combining multiple selected beamforming vectors for each UE, where the beam combination process is divided into wideband beam group construction and subband combination coefficients acquisition. Simulation results demonstrate that the proposed scheme could achieve considerable increase in the system throughput while maintaining acceptable feedback overhead.
BiDAF and QANet Model Variations on SQuAD2.0 Stanford CS224N Default Project IID SQuAD track

In this paper we build two models for the question-answering task on SQuAD 2.0 dataset: BiDAF (Bi-Directional Attention Flow) network and QANet. Based on vanilla BiDAF baseline model we first adopt coattention mechanism from Dynamic Coattention Network into BiDAF. Secondly we re-implement QANet. These two models get 61.855/62.309 EM and 65.309/65.595 F1 on development set respectively. Fusing Performer technique into QANet is also explored. Finally, we use a voting scheme ensemble model to achieve F1 = 68.35 on dev set and F1 = 65.69 on test set 1 .
Where Does the Patient Fit? An Analysis of Word Use Within the Context of Interprofessional Collaborative Care

Patient-centeredness is considered central to interprofessional collaborative patient care as a participatory, partnered approach between health care professionals and patients. Content analysis of 501 articles from the 1986, 1987, 1988, 1996, 2006, 2013, 2014, and 2018 volumes of a selected journal was undertaken. The purposes were to identify contexts in which the term patient was used in articles with a primary focus on interprofessional care and to identify trends in its usage. With Dilthey’s ideas on language as a framework, patient and its variations in the articles were coded under five categories. Findings suggest that the term patient appears predominantly as a modifier for activities enacted by experts and a platform for the discussion of relationships among professionals. There is limited evidence that use of the term patient fits within the context of partnership, suggesting that the language in published interprofessional collaborative research and discussion is currently largely expert, not patient-centered.
Common Sports Injury in Football Players: A Review

Football is the most popular sport worldwide, played by athletes of all ages, it is associated with a high injury rate. The injuries occur during football games and practice due to a combination of high speed and full contact. The authors of different studies showed in their results that the incidence of football injuries a range from 0.5 to 45 injuries per 1000 hours of practice and games. Football injuries most commonly affect the knee and ankle joints, muscles, and ligaments of the thigh and calf. Most commonly affected region is lower extremity with an incidence of 61% to 90%. There are two types of risk factors intrinsic and extrinsic risk factors which are responsible for football injury. We found through this review of literature that ankle injuries are the most common injuries in football players. Other injuries which is also common in football players are such as, ligament of knee, hamstring strain, football concussion, wrist injury. Keywords: Footballers, Sports injury, High speed, Injury incidence.
Lumbopelvic stabilization versus Pilates exercises on spatiotemporal gait parameters in chronic nonspecific low back pain

Aim of the work: The purpose of the current study is to trace and investigate how lumbopelvic stabilization and Pilates exercises affect the spatiotemporal aspects of gait in persistent nonspecific low back pain cases (NS-CLBP). Methods: Patients with NS-CLBP (N=90) were randomly assigned to one of three groups: group A (stabilization + traditional therapy), group B (Pilates plus traditional therapy), and group C (conventional therapy) in a single-blinded randomized clinical trial with 12 treatments over six weeks. A Walkway pressure measurement system was used to determine both spatial and temporal parameters. The Visual Analog Scale, Modified Oswestry Disability Questionnaire, Biering–Sorensen test, and trunk flexion endurance test were adopted successfully to assess pain, function, and isometric endurance of trunk extensor and flexor. Results: According to a cross-group analysis, a statistically significant effect was found when p = 0.001 and f-value = 3.12. Also, a statistically clear interaction was figured out between treatment and time when p = 0.0001 and f-value = 3.44. Following therapy, the Pilates group showed a decrease in temporal parameters, pain, and functional impairment, as well as an increase in cadence and velocity (p 0.05).
A review on tin dioxide gas sensor: The role of the metal oxide doping, nanoparticles, and operating temperatures

Metal oxide gas sensors have many advantages over other solid-state gas monitoring devices, including low cost, ease of manufacture, and small design. However, the shape and structure of sensing materials have a considerable impact on the performance of such sensors, posing a significant challenge for gas sensing properties on materials or dense films to attain high-sensitivity characteristics. Various tin dioxide (SnO2) nanostructures have been devised to increase gas sensing characteristics such as sensitivity, selectivity, and response time, among other characteristics. An overview of the most well-known techniques for synthesizing gas-sensing films, as well as the influence of doping with various metal oxides, nanoparticle size, and operating temperature on the gas-sensing properties of such films, is discussed in this work. The gas sensing mechanisms and the gas detection techniques are presented in detail. The metal oxide doped SnO2 showed a strong response for SO2 and NO2 gases, whereas nanoparticle doping plays a crucial effect in increasing SnO2 sensitivity towards H2, H2S, NO2, CO, Ethanol, etc. Furthermore, the effect of operating temperature on SnO2 response is discussed in this report. SnO2 has a high sensitivity over a wide temperature range (100-350 °C).
Development of DC Transfer Switch in Ultra High Voltage DC Transmission Systems

Considered as the key component in the HVDC transmission systems,the DC transfer switch needs to interrupt the DC current,which is different in a way that DC current does not show natural zero current point;to interrupt the dc current,one has to form the current to a zero point in order to quench the arc.In this paper,a DC transfer switch based on passive self-oscillation principle was developed.The goals of the transfer switch used in UHVDC transmission systems were proposed,and the technique route of developing this transfer switch was given.Though theoretical analysis and simulation calculation,the parameters of the component of the transfer switch were selected.To verify the function of the interrupting DC currents,a test system was established.The developed prototype of the transfer switch performed well in the test,interrupted 5.3kA DC current,satisfied the requirement of UHVDC transmission systems.The characteristic of surge arrester was verified by the residual voltage test and the energy absorb test.
AUTO-SCALING AND ADJUSTMENT PLATFORM FOR CLOUD-BASED SYSTEMS

For customers of cloud-computing platforms it is important to minimize the infrastructure footprint and associated costs while providing required levels of Quality of Service (QoS) and Quality of Experience (QoE) dictated by the Service Level Agreement (SLA). To assist with that cloud service providers are offering: (1) horizontal resource scaling through provisioning and destruction of virtual machines and containers, (2) vertical scaling through changing the capacity of individual cloud nodes. Existing scaling solutions mostly concentrate on low-level metrics like CPU load and memory consumption which doesn’t always correlate with the level of SLA conformity. Such technical measures should be preprocessed and viewed from a higher level of abstraction. Application level metrics should also be considered when deciding upon scaling the cloud-based solution. Existing scaling platforms are mostly proprietary technologies owned by cloud service providers themselves or by third parties and offered as Software as a Service. Enterprise applications could span infrastructures of multiple public and private clouds, dictating that the auto-scaling solution should not be isolated inside a single cloud infrastructure. The goal of this paper is to address the challenges above by presenting the architecture of Auto-scaling and Adjustment Platform for Cloud-based Systems (ASAPCS). It is based on open-source technologies and supports integration of various low and high level performance metrics, providing higher levels of abstraction for design of scaling algorithms. ASAPCS can be used with any cloud service provider and guarantees that move from one cloud platform to another will not result in complete redesign of the scaling algorithm. ASAPCS itself is horizontally scalable and can process large amounts of real-time data which is particularly important for applications developed following the microservices architectural style. ASAPCS approaches the scaling problem in a nonstandard way by considering real-time adjustments of the application logic to be part of the scalability strategy if it can result in performance improvements.
Hubungan Antara Lokus Kendali Internal dan Strategi Coping Stress Berfokus Masalah pada Karyawan PHK

Abstract This study aims to determine the correlation between the internal locus of control and problem focused of coping on lay off employees at PT. Panca Patriot Prima. The research method used is a quantitative approach with a descriptive correlational approach. The population in this study were lay off employees at PT. Panca Patriot Prima. The sampling technique used was purposive sampling. The sample in this study amounted to 50 employees who experienced layoffs. The instrument used was a modified internal control locus scale from the Levenson IPC scale and problem focused of coping scale prepared by the researcher. The results of this hypothesis test use Pearson Product Moment correlation. The results of this study indicate that internal locus of control and problem focused coping of lay off employees at PT. Panca Patriot Prima is at a very high range of norms. Correlation between internal locus of control and problem focused coping of lay off employees at PT. Panca Patriot Prima, Kab. Pasuruan is positive and significant with a significance value of 0.046 (less than 0.05). Penelitian ini bertujuan untuk mengetahui hubungan antara lokus kendali iternal dan strategi coping stres berfokus masalah pada karyawan PHK di PT. Panca Patriot Prima. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan pendekatan deskriptif korelasional. Populasi pada penelitian ini adalah karyawan PHK di PT. Panca Patriot Prima. Teknik sampling yang digunakan adalah purposive sampling. Sampel dalam penelitian ini berjumlah 50 karyawan yang mengalami PHK. Instrumen yang digunakan adalah skala lokus kendali internal yang dimodifikasi dari skala IPC Levenson dan skala strategi coping stres berfokus masalah yang disusun oleh peneliti. Hasil uji hipotesis ini menggunakan korelasi Pearson Product Moment. Hasil penelitian ini menunjukkan bahwa lokus kendali internal dan strategi coping stres berfokus masalah karyawan PHK di PT. Panca Patriot Prima berada pada rentangan norma sangat tinggi. Hubungan lokus kendali internal dan strategi coping stres berfokus masalah karyawan PHK di PT. Panca Patriot Prima Kab. Pasuruan adalah positif dan signifikan dengan nilai signifikansi sebesar 0,046 (kurang dari 0,05).
Hydrogels Made up of Natural Gums Based on Polysaccharides for Applications in Biomedicine: Brief Review

Natural gums based on polysaccharides such as guar gum, gum arabic and xanthan gum possess structure and properties that have been used for various applications in pharmaceutical, food and biomedicine. Due to their high presence of hydroxyl and/or carboxylate groups in their glycosidic skeletons, they can retain water molecules, forming matrices in the hydrogel state. These hydrogels have high biocompatibility that has been exploited in the biomedical field in strategies as controlled release of therapeutic agents, regenerative medicine, tissue engineering and modulation of cell growth. The objective of this review is to detail the chemical characteristics of natural gums and their use for the design of different hydrogel systems for applications in biomedicine.
Building a Low-Cost and Low-Fidelity Kidney Transplant Model: A Technical Report on the San Antonio Kidney Transplant Model

One of the most challenging aspects of the kidney transplant operation is performing vascular anastomoses in the confines and depths of the iliac fossa. General surgery residents need to be adequately trained in this skill to maximize their intraoperative experience during their transplant surgery rotation. While several kidney transplant models have been developed, they are limited in their ability to simulate the challenges of performing anastomoses at varying depths and in confined spaces. Furthermore, they may be expensive or require specialized equipment, such as three-dimensional printers, to build. In this technical report, we describe how to build a low-fidelity, low-cost, and portable kidney transplant model capable of simulating vascular anastomoses at varying depths. Our model can be easily replicated for less than 30 USD using materials available in local stores. It uses inexpensive and reusable parts, allowing trainees a high volume of repetitions.
An Assessment of Training as a Tool for Developing Human Resources in Federal Radio Corporation of Nigeria

Many studies show that professional on-work training and retraining are crucial in achieving proficiency for organisations. The quality and sustainability of an organisation depends on its regular and adequate training and development of its employees. Therefore, organisations that judiciously invest in training and development of their employees stand to realise increase in their competency, motivation, dedication and commitment to work. This study examines the perceptions of the sta ff attending the Federal Radio Corporation of Nigeria’s ( FRCN ) training programme and seeks to indicate “training” as a veritable tool for developing proficient human resources for broadcasting industry in Nigeria. The objectives are achieved through a methodical collection and collation of data in the Corporation. The results validate training as the e ff ective tool for improving productivity, innovation and the motivation of the sta ff in FRCN .