Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual Search and Decluttering in Tactical Situation Displays: A Computational Modeling Approach

Clutter in tactical situation displays (TSD) is a persistent problem that affects pilots’ performance. Decluttering methods such as dimming, dotting, small-sizing and removal have been used in several display types to reduce clutter. This study aims to investigate the effects of different decluttering methods applied in TSD on pilots’ visual search performance. It also aims to uncover the basic psychophysical processes underlying the pilots’ visual search behavior through computational modeling. Data from fifteen Air-Force pilots showed that accuracy is higher and response time is faster when the TSD is decluttered, regardless of the technique. However, when the data was fitted into the hierarchical drift-diffusion model, it was revealed that among the techniques tested, dimming yielded the best search performance based on the model parameters. This study suggests that analyzing behavioral data through computational modeling may lead to better insights that are more practical and applicable in solving the issues in visual search in TSDs.
A Novel Multiclad Single Mode Optical Fibers for Broadband Optical Networks

The demand for data communication is growing rapidly due to the increasing popularity of the Internet and other factors [1]. The unprecedented success of information technology in recent years ushers an explosive growth in demand for the Internet access in the 21st century. Ultra-wideband transmission media are needed in order to provide high-speed communications for a much larger number of users. A promising solution to the capacity crunch can come from wavelength-division-multiplexed optical fiber communication systems that are shown to provide enormous capacities on the order of terabit per second over long distances. These systems utilize single-mode fibers, in conjunction with erbiumdoped fiber amplifiers, as the transmission medium [2]. The optical silica fiber might be the only proper choice to realize this task. Optical fiber based communication is the excellent alternative for these purposes which needs low dispersion as well as dispersion slope and large bandwidth supported by optical physical medium[3]. Optical transmission began to be used in trunk cables about 1990; the capacity of those systems was several hundred Mbit/s per fiber. The capacity jumped to 2.5 (5.0) Gbit/s per fiber with the introduction of optical repeaters using erbium-doped fiber amplifiers in 1995. It jumped again in 1998, to 10 (20) Gbit/s per fiber, with the introduction of wavelength division multiplexing (WDM) [5]. Overall transmission capacity now exceeds 100 Gbit/s per fiber due to improvements in WDM techniques [6]. Usually, those techniques are called dense WDM (DWDM). In recent years, the increasing demands for transmission capacity have led to intense research activities on high capacity DWDM communication system [7]. Nowadays, applications such as optical time division multiplexing (OTDM) and dense wavelength division multiplexing (DWDM) are usual tasks in industry [1]. Therefore by considering these applications, providing a large bandwidth and high-speed communication possibility using optical fibers is highly interesting [3]. In the following, we review requirements for DWDM, Dispersion properties, optical nonlinearity, loss properties, and design of optical fiber for DWDM.
On Some Aspects of the Examination in Econometrics

Teaching econometrics has been studied by a number of researchers, however, there is little information available on the quality of examination and on simplification of tests for demonstration the high-quality knowledge by students in concrete topics of econometrics or mathematical economics.One can note the following main goals of studying the basics of mathematical economics or econometrics by students: forming the notions of mathematical model and of modeling economic processes and phenomena; understanding a role of using mathematical models for economics research and obtaining scientific results; formatting skills for constructing mathematical models in economics, for solving economics problems by mathematical modeling.The main goal of this paper is to simplify test tasks, is to help to students to demonstrate the high-quality knowledge in certain areas of mathematical economics, and also is to construct a system of testing tasks, in which the emphasis was placed on the knowledge and understanding of an algorithm of solving the problem.In the present paper, to quality examine the student knowledge in the basics of mathematical economics, a certain system of tests was constructed and is considered. The main attention is also given to algorithms and techniques of solving some tasks (problems) of mathematical economics. The following topics of mathematical economics are viewed: constructing mathematical models of linear programming, the input-output model, the Monge-Kantorovich transportation problem, the simplex method of linear programming, the graphic method of linear and nonlinear programming, the method of Lagrange multipliers in mathematical optimization. Some primary basic results of studying linear programming, nonlinear programming, and the input-output model are noted.A new system of tests that satisfies the aim of this paper is modeled. The described tests require less time for solving than usual tasks. Here we do not focus on the repetition of auxiliary mathematical knowledge and arithmetic skills. These tests are simplified versions of standard tasks and help students to demonstrate knowledge in the mentioned topics of mathematical economics. The tasks are focused only on the knowledge of basic formulas, techniques, and connections between mathematical objects, economic systems, and their elements.
Land Use and Land Cover Change Detection Using Remote Geospatial Techniques: A Case Study of an Urban City in Southwestern, Nigeria

Many cities in developing countries are experiencing ecosystem modification and change. Today, about 10 million hectares of the world’s forest cover have been converted to other land uses. In Nigeria, there is an estimated increase of 8.75 million ha of cropland and decrease of about 1.71 million ha of forest cover between 1995 to 2020, indicating that Nigeria has been undergoing a wide range of land use and land cover changes. This paper analyses the changes in land use/cover in Ila Orangun, Southwestern, Nigeria from 1986 to 2018, with a view to providing adequate information on the pattern and trend of land use and land cover changes for proper monitoring and effective planning. The study utilized satellite images from Landsat 1986, 2002 and 2018. Remote sensing and Geographical Information System techniques as well as supervised image classification method were used to assess the magnitude of changes in the city over the study period. The results show that 26.36% of forest cover and 44.48% of waterbody were lost between the period of 1986 and 2018. There was a rapid increase in crop land by 365.7% and gradual increase in built-up areas by 103.85% at an annual rate of 3.25%. Forest was the only land cover type that recorded a constant reduction in areal extent. The study concluded that the changes in land use and land cover is a result of anthropogenic activities in the study area.
Kano Model Integration with Data Mining to Predict Customer Satisfaction

The Kano model is one of the models that help determine which features must be included in a product or service to improve customer satisfaction. The model is focused on highlighting the most relevant attributes of a product or service along with customers’ estimation of how the presence of these attributes can be used to predict satisfaction about specific services or products. This research aims to develop a method to integrate the Kano model and data mining approaches to select relevant attributes that drive customer satisfaction, with a specific focus on higher education. The significant contribution of this research is to solve the problem of selecting features that are not methodically correlated to customer satisfaction, which could reduce the risk of investing in features that could ultimately be irrelevant to enhancing customer satisfaction. Questionnaire data were collected from 646 students from UAE University. The experiment suggests that XGBoost Regression and Decision Tree Regression produce best results for this kind of problem. Based on the integration between the Kano model and the feature selection method, the number of features used to predict customer satisfaction is minimized to four features. It was found that ANOVA features selection model’s integration with the Kano model gives higher Pearson correlation coefficients and higher R2 values.
Cardiovascular Autonomic Function in Individuals with Rheumatoid Arthritis

Rheumatoid arthritis is common inflammatory arthritis arising throughout the world. A chronic systemic inflammatory autoimmune disorder is known as Rheumatoid arthritis (RA). Principally it affects the joints and usually accompanied by one or more of extra-articular manifestations as rheumatoid nodules, neuropathy and norm chromic normocytic anemia. Rheumatoid arthritis can start at any age, but has maximum between 35 to 55 years of age. The prevalence of RA is about 1% worldwide whereas India is 0.9% with women suffering 3-5 times more than men. Sympathetic and parasympathetic involvement has described in primary and secondary vasculitis processes, as in systemic vasculitis processes like: SLE, RA. Peripheral nervous system is the main target in RA patients where as involvement of central nervous system (CNS) is rare. The aim of this study was to evaluate cardiac autonomic function in RA and compare with healthy individuals by using HRT analysis. Materials and Methods: A cross-sectional study was performed which was carried out in the Dept. of Physiology at Zydus Medical College and Hospital. It was carried out on both males and females of mean age group 45±10 years to study autonomic functions in RA. Total 50 individuals were include in which 25 were included as healthy individuals with not on any medication, served as controls and 25 were diagnosed with RA, on the basis of criteria developed by American College of Rheumatology along with sex matched controls. Details of history and examination were recorded on Performa. Patients were examined for signs and symptoms of possible Autonomic Nervous System (ANS) dysfunctions. Result: 50 individuals were include in this study which were grouped into Study group (Group – A) and Control group (Group – B). Group – A consisted of 25 individuals who were diagnosed with rheumatoid arthritis on basis of criteria developed by American College of Rheumatology. Group – B consisted of 25 healthy individuals not on any medication as to explain normal changes. The 30:15 ratio and valsalva maneuver demonstrated a less decrease but was non-significant statistically in the patients with Rheumatoid Arthritis as compared to control (p>0.05). On standing the blood pressure response the change in diastolic blood pressure was significantly (P<0.01) lower in groups A as compared to control. Conclusion: Cardiovascular autonomic function tests in routine clinical examination helpful in early detection of autonomic dysfunction in this disease. Further comprehensive information are useful about autonomic function may be extracted from global evaluation of all tests performed. Therefore testing of autonomic function may be the part of routine clinical evaluation in RA to reduce the cardiovascular autonomic morbidity.
Discovery of Rare Dying Radio Galaxies Using MeerKAT

Dying radio galaxies represent a stage of the evolution of active galactic nuclei (AGN), during which the accreting central black hole has switched off and/or falls to such a low level that the plasma outflow can no longer be sustained. When this happens, the radio source undergoes a period of fading, the dying phase, before it disappears completely. We present the study of three potential dying radio sources using the MeerKAT radio telescope: MKT J072851.2-752743, MKT J001940.4-654722, and ACO 548B. The identification as dying radio sources came from the MeerKAT Galaxy Cluster Legacy Survey (MGCLS). We carry out a multi-wavelength analysis of the sources and derive their energetics. The ages of the sources are ∼30–70 Myr, they have magnetic fields of the order of a few μG, and they have relatively low radio power. Their potential optical counterparts are associated with massive galaxies. We show that ACO 548B, previously classified as two peripheral relic radio sources, is a dying radio galaxy. With its good sensitivity and resolution, MeerKAT is an ideal instrument to detect potential dying radio sources, and contribute to the understanding of the evolution of AGN population.
Correlation of Sunlight Exposure and Different Morphological Types of Age-Related Cataract

Purpose The previous lab and clinical studies of the correlation between the ultraviolet B and age-related cataract (ARC) did not reach in the universal agreement, especially in different morphological types of ARC. It is important to systemically summarize those previous data of epidemiological studies, which might penetrate the relevance between three morphological types of ARC, cortical, nuclear, and posterior capsular (PSC), with sunlight exposure. Methods PubMed, Web of Science, CNKI, Embase, and Cochrane were searched online. Data were extracted and recalculated, and quality check was performed by hand. Review Manager was used to perform the fixed effects meta-analysis on ARC and its morphological types. The highest exposed dose group was defined as the exposed group, and the lowest dose group as the control group as possible. Results Finally, the number of analyzed studies was 31: 20 for ARC and twelve, eleven, and nine for the morphological types cortical, nuclear, and PSC, respectively. The pooled OR for ARC was 1.15 (range 1.00~43.78, 95% CI 1.09 to 1.21). The cortical cataract revealed a slightly higher risk, and pooled OR was 1.03 (range 0.67~2.91, 95% CI 1.02 to 1.03). But the pooled OR for nuclear and PSC were 1.00 (range 0.50~5.35, 95% CI 1.00 to 1.00) and 0.99 (range 0.57~1.87, 95% CI 0.95 to 1.01), respectively. Conclusions The systemic analysis of epidemiological articles reported till now reveals a significantly increased risk of ARC for those exposed with more sunlight, especially the morphological type of cortical cataract.
Can we teach without giving classes

More than ever, in the 21 century, is essential to acquire competences to learn, to find and manage the information that is needed to solve the anticipated problems or the unpredictable ones. Teaching must be organized towards the acquisition of these competences (basic skills), providing to students activities in which their commitment, responsibility and critical exercise of freedom are essential. I briefly present a case of teaching, at the university, based on negotiation and project work. The teams have created e-portfolios (open portfolios on the internet, blogs) and only 5 of the face-to-face 48 hours were expository (lectures by the professor). The approach has generated interest and high motivation and allowed the proper production and construction of knowledge by the students
Bioremediation of Uranium- and Nitrate-Contaminated Groundwater after the In Situ Leach Mining of Uranium

Uranium and nitrate are common groundwater pollutants near in situ leach uranium mines. However, we still lack techniques that can simultaneously immobilize uranium and reduce nitrate using a single bacterial species. In this study, the potential of simultaneous uranium immobilization and nitrate reduction by a single AFODN (anaerobic Fe(II) oxidizing denitrifier), Clostridium sp. PXL2, was investigated. Clostridium sp. PXL2 showed tolerance to U(VI) concentrations varying from 4.2 µM to 42 µM. The U(VI) immobilization and nitrate reduction rates in groundwater samples inoculated with this bacterium reached up to 75.1% and 55.7%, respectively, under neutral conditions. Exposure to oxidation conditions led to further U(VI) removal but did not show any noticeable effect on nitrate reduction. The U(VI) immobilization rate reached up to 85% with an increased Fe(II) initial concentration, but this inhibited nitrate reduction. SEM (scanning electron microscopy) coupled with EDS (energy dispersive spectroscopy) showed that the U(VI) immobilization was mainly due to sorption to amorphous ferric oxides. U(VI) and nitrate bioremediation by AFODNs, including Clostridium sp. PXL2, may provide a promising method for the treatment of uranium- and nitrate-contaminated groundwater after the in situ leach mining of uranium.
Perspective of Combustion Modeling for Gas Turbine Combustors

• Empirical/analytical design tools A status summary report is given on the development of comprehensive computational combustor design (CCD) tool activities of GEAE combustion group conducted for the last three years. A “no-fudge factor” pretest prediction approach is being pursued for the combustors that use rich or lean-dome swirl cups (Single Annular and Dual Annular combustors, SAC, DAC); Twin Annular Premixing Swirler, TAPS (SAC and DAC), and Dry Low Emissions’ DACRS mixers for triple annular combustor domes. The pretest prediction capability is being gauged with existing data including emissions, exit temperature quality and wall temperatures from nine different combustors selected from a group of production and technology combustors. The agreement between predictions and data is good considering this is the 1 st
PV Performance Modeling Workshop Summary Report

During the development of a solar photovoltaic (PV) energy project, predicting expected energy production from a system is a key part of understanding system value. System energy production is a function of the system design and location, the mounting configuration, the power conversion system, and the module technology, as well as the solar resource. Even if all other variables are held constant, annual energy yield (kWh/kWp) will vary among module technologies because of differences in response to low-light levels and temperature. A number of PV system performance models have been developed and are in use, but little has been published on validation of these models or the accuracy and uncertainty of their output. With support from the U.S. Department of Energy's Solar Energy Technologies Program, Sandia National Laboratories organized a PV Performance Modeling Workshop in Albuquerque, New Mexico, September 22-23, 2010. The workshop was intended to address the current state of PV system models, develop a path forward for establishing best practices on PV system performance modeling, and set the stage for standardization of testing and validation procedures for models and input parameters. This report summarizes discussions and presentations from the workshop, as well as examines opportunities for collaborative effortsmore » to develop objective comparisons between models and across sites and applications. « less
Usability issues with electronic health records: Is it even worth it for human factors practitioners?

Despite the need for addressing usability issues within Electronic Health Records (EHR), health care organizationshave struggled to systemically involvehuman factors practitioners (HFP). Thereare several challenges to supporting EHR-related work as HFP. Simple design changes mayhavedependencies or create downstream consequences that are not typical of other software systems, or not be feasible to change without overhaul of functionality from theEHR vendor. This panel will present successes and lessons learned bya group of HFP embeddedin healthcare systemswho have extendedexperience working on EHR configurationand design changes. They will discuss challengesand strategies in adopting human factorstechniquesto improve EHR design and related outcomes. By the end of the panel, audience members will learn not only howhuman factors is having animpact in this aspect ofhealthcare delivery, but also learn approaches that may be applicable to other complextechnical systems.
PRAKIRAAN CUACA DENGAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGENEURAL NETWORK, DAN ADAPTIVE SPLINES THRESHOLD AUTOREGRESSION DI STASIUN JUANDA SURABAYA

The need of weather forecasting is primary to support activities in various sectors, so the efforts of development for forecast methods to improve the precision and the accuracy of the weather information are very important. Various weather forecasting models by engineering or stochastic model approach have been developed, although each method has both weaknesses and strengths, the efforts for developing techniques or methods to get the best model have to be done. What is elaborated in this article represent the result of testing in three statistical methods to obtain the best weather forecasting models. Three methods as mentioned before are: the Autoregressive Integrated Moving Average (ARIMA), Neural Network (NN), and Adaptive Splines Threshold Autoregression (ASTAR) to forecast the temperature, humidity, and daily rainfall. The performance of these three methods are evaluated by correlation values and Root Mean Square Error (RMSE). The good performance characterized by a high correlation between actual and forecast values, and also has a small RMSE. The results of this research indicate that ASTAR method produces better signed by a higher correlation, lower RMSE values and the constant forecasting from the first day until the thirtieth. The correlation in ASTAR method for Tmax and RHmin respectively are 0,70 and 0,75, for ARIMA method are 0,31 and 0,47, for NN method are 0,02 and -0,06. The three methods have poor performance for Tmin, RHmax and RRR. Keywords: Weather forecast, ARIMA, ASTAR, Neural Network
Exploring Reliability of Gold Labels for Emotion Detection in Twitter

Emotion detection from social media posts has attracted noticeable attention from natural language processing (NLP) community in recent years. The ways for obtaining gold labels for training and testing of the systems for automatic emotion detection differ significantly from one study to another, and pose the question of reliability of gold labels and obtained classification results. This study systematically explores several ways for obtaining gold labels for Ekman’s emotion model on Twitter data and the influence of the chosen strategy on the manual classification results.