Optimizing an F-16 Squadron Weekly Pilot Schedule for the Turkish Air Force

Fighter squadrons in the Turkish Air Force build flight schedules for weekly periods. This process requires a great deal of time and does not seek optimality. Schedules are built with feasibility concerns. The Turkish Air Force doesn’t have an automated tool for flight scheduling. Many constraints including crew rest, number of sorties flown in a month, and duty currencies affect the schedule. Providing an automated scheduling tool may help schedulers save time for other squadron tasks including mission preparation, briefing, and debriefing. In this research, a heuristic approach to the problem is developed. Greedy Randomized Adaptive Search Procedures (GRASP) is applied to the weekly pilot scheduling problem. Manual scheduler inputs are allowed. A code for GRASP implementation is written in MATLAB. Two different approaches are used in the analysis. First, the code is run for four weekly schedules taken from an F-16 squadron of the Turkish Air Force and second, a weekly flight schedule is created randomly. In the second approach, the created flight schedule is used for three different scenarios which represent possible real life situations. For all scenarios and real schedules, GRASP performed well and smaller standard deviations in sortie numbers are obtained while keeping all pilots within the currency limit of each mission

What does a measurement of mass and/or radius of a neutron star constrain: Equation of state or gravity?

Neutron stars (NSs) are thought to be excellent laboratories for determining the equation of state (EoS) of cold dense matter. Their strong gravity suggests that they can also be used to constrain gravity models. The mass and radius (M-R) of a NS both depend on the choice of EoS and gravity, meaning that NSs cannot be simultaneously good laboratories for both of these questions. A measurement of M-R would constrain the less well known physics input. The assumption that M-R measurements can be used to constrain EoS-presumes general relativity (GR) is the ultimate model of gravity in the classical regime. We calculate the radial profile of compactness and curvature (square root of the full contraction of the Weyl tensor) within a NS and determine the domain not probed by the Solar System tests of GR. We find that, except for a tiny sphere of radius less than a millimeter at the center, the curvature is several orders of magnitude above the values present in Solar System tests. The compactness is beyond the solar surface value for r>10 m, and increases by 5 orders of magnitude towards the surface. With the density being only an order of magnitude higher than that probed by nuclear scattering experiments, our results suggest that the employment of GR as the theory of gravity describing the hydrostatic equilibrium of NSs is a rather remarkable extrapolation from the regime of tested validity, as opposed to that of EoS models. Our larger ignorance of gravity within NSs suggests that a measurement of M-R constrains gravity rather than EoS, and given that EoS has yet to be determined by nucleon scattering experiments, M-R measurements cannot tightly constrain the gravity models either. Near the surface the curvature and compactness attain their largest values, while EoS in this region is fairly well known. This renders the crust as the best site to look for deviations from GR.Comment: Phys.Rev. D published, typos corrected to match the published versio

THE EFFECT OF FAN’S BRAND TRUST ON BRAND LOYALTY

The aim of this study is to analyze and evaluate the determination of trust and loyalty level of basketball fans to their team and to help form strategic sales plan considering the trust and loyalty level of fans to their team. The data from the survey are generated from 283 fans ranging in age from 13 to 71 (205 male, 78 female) who participate in basketball games. As a result of the structural equation modelling, it has been found that brand trust has a positive and strong effect on attitudinal loyalty and attitudinal loyalty has a positive and strong effect on behavioral loyalty. According to the research results, the increase in the brand trust of fans may cause an increase in brand loyalty and thus contributing to the achievement of both financial and marketing aims. The financial aims of sports teams may be listed as profitability, increasing the market share, leading the price, licensed product sales, matchday revenues, increasing concessions/catering and providing high-quality services. On the other hand, the marketing purposes may be listed as increasing recognition, fan/customer retention, gaining new fans, developing new products, strengthening the brand, and increasing the brand value. When considered in these terms, obtaining the trust of the fans has crucial importance.  Article visualizations

Oryantiring Uygulamalarının 6. Sınıf Öğrencilerinin Akademik Başarı ve Harita Okuryazarlık Düzeylerine Etkisi

This study aimed to examine the effects of orienteering practices on the sixth-grade students' academic achievement and map literacy in social studies. As one of the mixed-method designs, this study adopted an experimental (intervention) design, which provides a means of integrating the qualitative approach into an experimental process. Fifty-three sixth-grade students from a secondary school in the eastern region of Turkey comprised the study sample. The study included an experimental group (n= 26) and a control group (n= 27). In the experimental group, the "People, Places, and Environments" unit was taught using orienteering techniques, whereas, in the control group, standard curriculum-based instruction was conveyed. The quantitative data were collected through the Academic Achievement Test (AAT) and Map Literacy Test (MLT), while a semi-structured interview protocol was used to gather the qualitative data. The experimental and control groups were administered the AAT and MLT as pre- and post-tests, and the SPSS 22.0 program was used for the analysis. The students' opinions in the experimental group regarding the orienteering practices were taken through a semi-structured interview protocol. The data obtained from these interviews were subjected to content analysis. The results show no statistically significant difference between the experimental and control groups on the pre-test regarding academic achievement and map literacy levels; however, there was a substantial difference in favor of the experimental group on the post-test. Additionally, the analysis of qualitative data showed that all of the stuBu çalışmanın amacı, sosyal bilgiler öğretiminde kullanılan oryantiring uygulamalarının öğrencilerin akademik başarı ve harita okuryazarlık düzeylerine etkisini belirlemektir. Araştırma, deneysel bir sürecin içine nitel yaklaşımın gömüldüğü karma araştırma yöntem desenlerinden biri olan, deneysel (müdahale) desene dayalı olarak yürütülmüştür. Araştırmanın örneklem grubunu, Erzurum ili Pasinler ilçesinde bulunan bir ortaokulda öğrenim gören 6. sınıftaki 53 öğrenci oluşturmaktadır. Araştırmada bir deney grubu (n= 26), bir de kontrol grubu (n= 27) yer almaktadır. Deney grubunda “İnsanlar, Yerler ve Çevreler” öğrenme alanında yer alan konuların öğretimde oryantiring uygulamaları kullanılırken; kontrol grubunda ise öğretim süreci, mevcut programa dayalı olarak yürütülmüştür. Araştırmada nicel veriler, Akademik Başarı Testi (ABT) ve Harita Okuryazarlık Testi (HOT), nitel veriler ise yarı yapılandırılmış görüşme formu aracılığı ile toplanmıştır. ABT ve HOT deney ve kontrol grubuna ön test ve son test olarak uygulanmış ve analizleri SPSS 22.0 paket programı ile yapılmıştır. Deney grubunda yer alan öğrencilerin oryantiring uygulamaları ile ilgili görüşleri yarı yapılandırılmış görüşme formu ile alınmıştır. Görüşme formundan elde edilen veriler içerik analizi yöntemi ile yorumlanmıştır. Araştırma sonucunda deney ve kontrol grubu arasında, akademik başarı ve harita okuryazarlık düzeyleri açısından ön testte istatistiksel olarak anlamlı bir farkın olmadığı, son testte ise deney grubu lehine anlamlı bir farkın olduğu tespit edilmiştir. Deney grubu ile yapılan yarı yapılandırılmış görüşme sonucunda, öğrencilerin tamamının oryantiring uygulamaları ile ilgili olumlu düşünceler geliştirdiği görülmüştür

Mermer türlerinin makine öğrenmesi teknikleri kullanılarak sınıflandırılması

Doğal taşlar, insanların barınmadan silaha kadar vazgeçilmez unsurlarından bir tanesidir. Bu taş türleri içerisinde mermerler ve mermer türevli ürünler banyodan mutfağa, bahçe tasarımından küçük dekoratif ev süslerine kadar insanların sürekli tercih ettiği objelerdendir. Mermerler çıkarıldıkları bölgelere göre isimlendirilirken bu alanda uzman olarak nitelendirilen kişiler tarafından gözleme dayalı olarak türleri ve kaliteleri sınıflandırılmaktadır. Uzman kişilerin gözleme dayalı yaptığı bu sınıflandırma ekonomik anlamda risk taşımakta, iş yükünü arttırmakta ve hata oranı yüksek olabilen zorlu bir süreçtir. Bu süreçlerin hızlı, kolay ve doğruluk oranı yüksek bir dijital dönüşüme ihtiyacı bulunmaktadır. Bu çalışmada mermerlerin tür sınıflandırmasında derin öğrenme kullanılarak özellik çıkarımı yapılmıştır. Çıkarılan özellikler makine öğrenme teknikleri kullanılarak sınıflandırma uygulaması gerçekleştirilmiştir. 28 ayrı türe ait 3703 mermer ve mermer türevli doğal taş imgesinden oluşan veri seti ile yapılan uygulamanın test sonucunda DenseNet derin öğrenme modeli ve K-En Yakın Komşu metodu ile %99,7’lik sınıflandırma başarımı elde edilmiştir.Natural stones are one of the indispensable elements of people from shelter to weapons. Among these stone types, marbles and marble-derived products are among the objects that people always prefer, from bathroom to kitchen, from garden design to small decorative home decorations. While the marbles are named according to the regions where they are extracted, their types and qualities are classified based on observation by people who are qualified as experts in this field. This classification, which is made by experts based on observation, carries risks in economic terms, increases the workload and is a difficult process with a high error rate. These processes need a fast, easy and highly accurate digital transformation. In this study, feature extraction was done by using deep learning in the species classification of marbles. The extracted features were classified using machine learning techniques. As a result of the application made with the data set consisting of 3703 marble and marble-derived natural stone images belonging to 28 different species, a classification success of 99.7% was obtained with the DenseNet deep learning model and the K-Nearest Neighbor method

THE EXAMINATION ACCORDING TO THE POSITION OF PLAYERS OF AEROBIC AND ANAEROBIC CAPACITY RELATION IN PROFESSIONAL FOOTBALL PLAYERS

The aim of this research is to examine the comparison of the aerobic and anaerobic capacity relationship according to positions of the professional football players (FP). The participants in this study were male FP (n = 32, Mage = 22.19, SD = 2.33, Mheight = 178 cm, SD = 0.04, Mweight = 73.05 kg, SD = 7.39, Mbodyfat %  = 9.01,  SD = 3.43, Mbodymasindex = 23.25,  SD = 2.23,) who professional trained regularly. They participated WAnT and shuttle run tests in order to measure anaerobic power (AnP) (MAnP = 14.31 watt/kg, SD = 1.57), anaerobic capacity (AnC) (MAnC = 7.5 watt/kg, SD = 0.4), maximal heart rate (HRmax ) (MHRmax = 179 beat per minute,  SD = 16.8) and maximal oxygen consumpt (VO2max ) (MVO’max = 51.8 ml/kg/min,  SD = 4.25). According the positions (defence – midfield and forward) of the FP, there isn't a statistical difference among HRmax, VO2max, AnP and AnC (p>0.05). There is no longer the concept of classical position in today's football so the features specific to classical position change. All of the footballers perform in both attack and defense. In accordance with the coach tactics, midfielder and striker blocks are constantly moving back and forth as the field is shrinks and so each player is about the same distances.  Article visualizations

Sülfür hekzaflorür molekülünün elektron etkisi ile iyonlaşma ikili diferansiyel tesir kesitlerinin ölçümü

Sulfur hexafluoride (SF6) is a widely used insulator in the industry, but it also has a high global warming potential. Studying electron impact ionization of SF6, particularly measuring the energy and angular distributions of the collision products, can provide valuable information about the underlying physics of the collision process and the nature of SF6 molecule. In this study, double differential cross sections (DDCSs) for electron impact ionization of SF6 have measured using a crossed beam experimental setup. The incident electron beam, with an energy range of 50-350 eV, was directed towards a target gas composed of SF6, and scattered electrons were detected as a function of the energy and scattering angle. The findings of this study offer significant insights into the molecular structure of SF6 and will contribute to enhancing the understanding of charged particle interactions involving SF6Sülfür heksaflorür (SF6), küresel ısınma potansiyeli olmasına rağmen yalıtkanlık özellikleri nedeniyle endüstride sık kullanılan bir gazdır. SF6'nın elektron etkisi ile iyonlaşma çalışmaları, özellikle çarpışma sonucu açığa çıkan parçacıkların enerji ve açısal dağılımlarının ölçülmesi, iyonlaşma sürecinin temel fiziksel özellikleri ve SF6 molekülünün yapısı hakkında değerli bilgiler sağlamaktadır. Bu çalışmada, SF6'nın elektron etkisi ile iyonlaşma olayı için ikili diferansiyel tesir kesiti (DDCS) ölçümleri yapılmıştır. SF6 molekülü 50-350 eV enerjili elektronlar ile çarpıştırılarak ortaya çıkan elektronlar enerji ve saçılma açısının fonksiyonu olarak dedekte edilmiştir. Bu çalışmanın bulguları, SF6'ın moleküler yapısı hakkında önemli bilgiler sunmakta olup, molekülün yüklü parçacıklar ile olan etkileşimlerinin anlaşılmasına katkı sağlayacaktır

Development of Early Stage Diabetes Prediction Model Based on Stacking Approach

Diabetes is a disease that may pose direct or indirect risks in terms of human health. Early diagnosis can minimize the potential harm of this disease to the body and reduce the probability of death. For this reason, laboratory tests are performed on diabetic patients. The analysis of these tests enables the diagnosis of diabetes. The aim of this study is so quickly diagnose diabetes by using data obtained from patients with machine learning methods. In order to diagnose the disease, k-nearest neighbor (k-NN), logistic regression (LR), random forest (RF) models and the stacking meta model which is created by combining these three models were used. The dataset used in the research includes test samples taken from 520 people. The dataset has 17 features, including 16 input features and 1 output feature. As a result of the classification through this dataset, different classification results were obtained from the models. The classification success of the models LR, k-NN, RF and stacking were found to be 91.3%, 91.7%, 97.9% and 99.6%, respectively. F-score, precision and recall performance metrics were utilized for a detailed analysis of the models\u27 classification results. The obtained results revealed that the stacking model has a sufficient level to be used as a decision support system in the early diagnosis of diabetes

The effect of growth potential on the self-discharge behavior of Cu–Ni based alloy electrodes

Recently, the increasing demand for sustainable clean energy from non-fossil sources motivated the researchers in energy storage devices and supercapacitors are one of the most promising energy storage systems. In this study, flexible copper and nickel coated electrodes are fabricated for supercapacitor applications from Ethaline deep eutectic solvent media. Copper and nickel-based materials were potentiostatically electrodeposited on flexible graphite substrates from Ethaline ionic liquid containing copper and nickel ions. Cu–Ni coated graphite films were scanned in 1 M KOH from −0.7 V to 0.4 V at different scan rates ranging between 5 mV s−1 and 100 mV s−1. Fabricated Cu–Ni electrodes were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). Copper and nickel formation ratios on graphite films at different deposition voltages were determined by EDX analysis. Cu–Ni coated graphite films applying −1.8 V deposition potential exhibited a maximum areal capacitance of 47.3 mF cm−2 at 5 mV s−1 scan rate. Galvanostatic charge-discharge curves of the electrodes obtained at different applied voltages confirms the supercapacitor behaviour of Cu–Ni coated films. One of the biggest issues regarding the use of supercapacitors in daily life is their self-discharge behaviour. Self-discharge curves of the Cu–Ni modified electrodes were illustrated that decreasing deposition potentials can decrease self-discharge problem. This research determines that Ethaline ionic liquid is a potential media for alloy-based electrodes in the usage of supercapacitor applications. © 2022 Elsevier Lt