Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection limit of fishing boats by the day night band (DNB) on VIIRS

The detection limit of DNB was proposed as a function of the brightness temperature (BT) at 3.7 μm, where the transmittance of cloud could be observed as a change of surface temperature. The shortwave infrared band exhibited a wide distribution in BT more than the thermal infrared band for the same level of DNB radiance. The lights from surface were identified even under the full Moon condition with the proposed method, where clouds were reflecting the lunar lights. A different distribution of clouds for day to day and a change of the Moon phase with its elevation make this problem more complicated. But the approach of contrast based evaluation of surface lights and lunar reflected lights could be one solution to distinguish the lights from the surface. Currently, a validation is necessary in the future to confirm this algorithm and to validate the detected pixels to be fishing boats with the stable light sources. The time series data of fishing boats could be studied to analyze the region of fishing area relative to the distribution of sea surface temperature and/or chlorophyll-a.
PENGARUH MODEL QUANTUM TEACHING TERHADAP HASIL BELAJAR SISWA PADA MATERI POKOK LISTRIK DINAMIS

Penelitian ini bertujuan untuk mengetahui pengaruh yang signifikan penggunaan model Quantum Teaching tehadap hasil belajar fisika pada materi pokok listrik dinamis. Jenis penelitian yang digunakan dalam penelitian ini adalah quasi eksperimen dengan desain penelitian two group pretes-postes. Populasi dalam penelitian ini adalah seluruh siswa kelas X SMA Kebangsaan Medan T.P. 2016/2017 yang terdiri dari 3 kelas dengan jumah 103 siswa. Pengambilan sampel dilakukan dengan teknik cluster random sampling, dimana siswa kelas X-1 dengan jumlah 33 siswa sebagai kelas eksperimen yang diajar dengan Model Quantum Teaching dan siswa kelas X-2 dengan jumlah 33.siswa yang diajar dengan Model pembelajaran langsung. Hasil penelitian untuk kelas eksperimen dan kelas kontrol menunjukkan bahawa data berdidstribusi normal dan homogen. Untuk uji kesamaan rata-rata pretes didapat memiliki kemampuan awal yang sama, dengan menggunakan uji t dua pihak. Kemudian diberi perlakuan untuk kelas eksperimen yang diajar dengan model Quantum teaching dan di kelas kontrol dengan model pembelajaran langsung dengan hasil nilai rata-rata postes untuk kelas eksperimen diperoleh 72 dengan standar deviasi 9,161 dan nilai rata-rata post-tes untuk kelas kontrol diperoleh 66,424 dengan standar deviasi 8,302. Dari hasil uji t satu pihak dapat disimpulkan ada pengaruh yang signifikan penggunaan model quantum teaching terhadap hasil belajar siswa pada materi pokok listrik dinamis siswa kelas X Semester II SMA Kebangsaan Medan
Curve Fitting and Optimal Design for Prediction

The optimal design problem is tackled in the framework of a new model and new objectives. A regression model is proposed in which the regression function is permitted to take any form over the space :! l' of independent variables. The design objective is based on fitting a simplified function for prediction. The approach is Bayesian throughout. The new designs are more robust than conventional ones. They also avoid the need to limit artificially design points to a predetermined subset of:! l'. New solutions are also offered for the problems of smoothing, curve fitting and the selection of regressor variables.
Skill assessment and optimization of the third generation wave models for applications in Gulf of Mexico

v CHAPTER 1: INTRODUCTION . 1 1.1 The Basic Physics of Third Generation Wave Models . 1 1.2 Open Source Third Generation Wave Models . 2 1.3 Preparation of General Data Used to Run a Wave Model . 3 1.4 Statistical Parameters Used for Evaluation . 6 1.5 Objectives . 7 1.6 Organization of Dissertation . 7 CHAPTER 2: EVALUATION OF TWO WAM WHITE CAPPING PARAMETERIZATIONS USING PARALLEL UNSTRUCTURED SWAN WITH APPLICATION TO THE NORTHERN GULF OF MEXICO, U.S.A. 9 2.
Perfect state transfer in unitary Cayley graphs and gcd-graphs

Abstract In this work, we consider the problem on the existence of perfect state transfer in unitary Cayley graphs and gcd-graphs over finite commutative rings. We characterize all finite commutative rings allowing perfect transfer to occur on their unitary Cayley graphs. Also, we use our main result to study perfect state transfer in unitary Cayley signed graphs and some gcd-graphs on quotient rings of unique factorization domains. Moreover, we can apply some calculations on the eigenvalues to determine the existence of perfect state transfer in Cayley graphs over finite chain rings.
The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models

ABSTRACT Uncertainty is a common problem in spatial modeling and geographical information systems (GIS). Furthermore, urban gain modeling (UGM) contains various dimensions and components of uncertainties. Data sampling is important in UGM, and may cause the results of the models to contain many uncertainties as well as affects their precision and accuracy. A poorly sampled or biased dataset can lead to inaccurate predictions and decreased performance of the models. This paper aims to present and develop novel strategies for sampling and building training datasets that can enhance the performance of data-driven models. In other words, the present study used maximum entropy (ME) and ecological niche factor analysis (ENFA) models to select pure non-change samples with minimal uncertainty for training datasets in UGM of Isfahan and Tabriz cities in Iran. The urban gain of two time intervals of 1992–2002 and 2002–2012 were used for Tabriz City and two time intervals of 1994–2004 and 2004–2014 for Isfahan City. Nine and 14 urban gain drivers were used in the UGM of Isfahan and Tabriz cities, respectively. After the ME and ENFA models produced a training dataset with change and non-change samples with the lowest uncertainty, three well-known models, namely random forest (RF), artificial neural network (ANN), and support vector machine (SVM) were used for the modeling. Moreover, the ME and ENFA models that were used to investigate the uncertainty of the sampling procedure were used as the one-class prediction models. Compared to extant studies, the proposed ME – based sampling strategy increased the area under the receiver operating characteristic curve (AUROC), figure of merit, producer’s accuracy, and overall accuracy by 5.5%, 5%, 5%, and 3%, respectively, in the validation phase of Isfahan City and by 5%, 6%, 14%, and 17%, respectively, for Tabriz City. For Isfahan, the accuracies of ME (AUROC = 0.649) and ENFA (AUROC = 0.661) one – class models were closer to that of the ANN – ME (AUROC = 0.646), ANN – ENFA (AUROC = 0.619), and RF – ENFA (AUROC = 0.631) models but differed significantly from that of the RF – ME (AUROC = 0.737) model. For Tabriz, the accuracies of ME (AUROC = 0.657) and ENFA (AUROC = 0.688) one – class models were lower than that of the two class RF-ME (AUROC = 0.852), and ANN-ME (AUROC = 0.778) models. The results showed that the ME model was able to identify relatively pure non-change samples and properly remove impure non-change samples from the training dataset. This study discovered that binary models are preferable to one-class models, and showed that an optimal sampling strategy is an essential step in UGM as it can decrease uncertainty. As such, modelers must adopt efficient sampling methods.
Utiliser les vibrations induites par vortex et la théorie du contrôle pour extraire de l'énergie d'un écoulement

We use an asymptotic model developed at low Reynolds numbers in order to investigate the forced dynamics of a circular cylinder experiencing vortex-induced vibrations. We analyze the orbit of the limit cycles prevailing at large times, and show that the magnitude of energy that can be harnessed from the flow can be optimized by applying a blowing and suction velocity at the cylinder wall, whose amplitude is proportional to the cylinder displacement. Mots clefs : vibrations induites ; récupération d’énergie ; contrôle
A SET OF NEW ALL-DIRECTION ROBUST REGULATION INDICES

A set of new all-direction regulation indices (ADRI) is suggested using the accustomedclassical geometrical terminology. With the advantage of the previous indices, they aresuitable for both simple-input simple-output systems and multi-input multi-output systems.Different from the tracking indices type, ADRI summarises the whole regulation specifica-tions of the system for various possible disturbances from all directions in the state space.The characters of the new and the old indices are analyzed. The algorithm of ADRI valuesis given. It is found that both the ADRI and the robustness index of a system simultaneouslyrequire the eigenvectors to be as orthonormal as possible. As a result a functional index isobtained that can improve the robustness and the dynamic regulation performance simulta-neously.
Personalbindung an Schulen in herausfordernden Kontexten - Kann transformationale Führung Kündigungsabsichten mildern?

Die Arbeit an Schulen in herausfordernden Kontexten ist von pädagogischen Herausforderungen geprägt, welche bei den Lehrpersonen zu Kündigungsabsichten führen können. Der Beitrag untersucht bei 1’658 Lehrpersonen aus 114 Schulen im Kanton Bern den Zusammenhang zwischen dem sozialräumlichen Kontext der Schule und der Kündigungsabsicht und überprüft, welche Rolle eine transformationale Führung durch die Schulleitung spielt. Die Ergebnisse zeigen, dass herausfordernde Umstände der pädagogischen Arbeit positiv und transformationale Führung negativ mit Kündigungsabsichten verbunden sind, die Effekte jedoch voneinander unabhängig auftreten. Das deutet darauf hin, dass transformationale Führung zur Personalbindung beiträgt, aber nicht unbedingt widrige Arbeitsbedingungen zu kompensieren vermag.
Rolling Bearing Signal Denoising Based on Wavelet Neighboring Coefficients Combined with Improved Shrinkage Threshold

In order to reduce noise in signal contaminated by strong noise, a joint denoising method wavelet adjacent coefficients combined with shrinkage threshold is proposed. The threshold function is improved to some extent. By adjustingthe parameters of the adjacent coefficients of the wavelet adaptively, after the decorrelation of wavelet adjacent coefficients combining it with the shrinkage threshold, the noise reduction experiment of the bearing simulation signals contaminated by strong noise is carried out. The experimental results show that the denoising effect of this method is better than one of the two methods used alone. The method is applied to the actual bearing fault diagnosis. The results show that the denoising method can effectively extract the characteristic frequency of bearing fault.
Mathematical modelling for academic performance status reports in learning analytics

The fast changing nature of the educational environment and the subsequent increase in the volumes of generated learner data, have found existing data analysis techniques lacking in certain fields. These techniques form part of the analysis and reporting phases of learning analytics and need to adapt to accommodate the changing face of education. In this paper, a set of interrelated algorithmic solutions that utilise mathematical programming models to generate and provide learning feedback in the form of academic performance status reports, is presented. Three existing mathematical models, more specifically the benchMark program, an outputs-only data envelopment analysis and a traditional analytic hierarchy process were evaluated for providing the information required to assist students in improving their academic achievement. The requirements include providing students with their current academic performance status, setting interim improvement goals and calculating improvement targets towards reaching those goals. The evaluated models did not address the requirements satisfactorily. The solution proposed in this paper consists of an algorithm that implements a linear programming model to generate performance status reports based on the current assessment scores of a group of students in a module. The output is used in a second algorithm that utilises the remaining improvement opportunities available to generate a participation future time perspective. The resulting schedule together with each individual student's current assessment scores, is used to calculate discrete improvement goals for each student as well as targets towards reaching those goals. A third algorithm provides a lecturer with some insight into the mastering of module content. Keywords: Analytic hierarchy process, data envelopment analysis, educational feedback, learning analytics, linear programming, non-linear programming
Exploring Motives for Twitch Viewership and Content Creation With the Exergame Zwift

Exergames require users to actively participate in sports in real time. Individuals taking part in exergames can use the livestreaming platform Twitch to create and view related content. This study employed uses and gratifications theory to examine Twitch usage and the motives of viewers and content creators of Zwift, a bicycling exergame. Thematic analysis of semistructured interviews with 10 Twitch users revealed viewers and content creators shared the motives of interaction and knowledge. Viewers also identified the motives of community, fandom, and competition as important, while content creators were additionally motivated by accomplishments, brand, and broadcasting. These findings align with previous research of Twitch usage and offer advice for practitioners. The study also highlighted the importance of studying the underinvestigated exergames, providing an opportunity to grow this participation.
Investigating the Impact of Social Media Usage on the Mental Health of Young Adults in Buffalo City, South Africa

In South Africa, social media usage has consistently increased over time, with young individuals being the most active users. However, there are concerns about mental illness, such as depression, as a result of the surge in social comparison. This study explored the relationship between social media usage and mental health among young adults in the Buffalo City Metropolitan Municipality. This study used a quantitative research approach and was based on the positivism paradigm. Data was collected from 127 young individuals aged 14 to 35 who live in the Buffalo City Metropolitan Municipality through the use of structured questionnaires. The data collected was analysed using a descriptive statistical package for the social sciences. The findings of the study amongst others showed that the young adults spend an average of 6 hours per day on social media platforms. Also, the fear of missing out (FoMO) was identified as another major reason why young adults stay on social media platforms for long hours every day. Based on the results presented in this study, one can convincingly state that the excessive use of social media is negatively contributing to the mental health status of young adults. Some of these detrimental impacts include depression, anxiety, low self-esteem, suicide and other mental health issues. The study recommends amongst others that an urgent and continuous well-structured awareness campaign be made to help sensitise the young adults on the danger of excessive use of social media platforms, both on their mental health status and life in general.
Densification of a-IGZO with low-temperature annealing for flexible electronics applications

Amorphous InGaZnO (a-IGZO) thin-film transistors are a leading contender for active channel materials in next generation flat panel displays and flexible electronics. Improved electronic functionality has been linked to the increased density of a-IGZO, and while much work has looked at high-temperature processes, studies at temperatures compatible with flexible substrates are needed. Here, compositional and structural analyses show that short term, low-temperature annealing (<6 h) can increase the density of sputtered a-IGZO by up to 5.6% for temperatures below 300 °C, which is expected to improve the transistor performance, while annealing for longer times leads to a subsequent decrease in density due to oxygen absorption.
'Useful' Renyi's Information Measure of Order α, Type β And Source Coding Theorem

A parametric mean length is defined as the quantity       1 1 log 1 i n i i u D i i u p D L u p                    , where   0 1 ,    0, 0, 1 i u D     is an integer,   1 i p . This being the useful mean length of code words weighted by utilities, i u . Lower and Upper bounds for u L  are derived in terms of ‘useful’ Renyi’s entropy of order  type  . AMS Subject classification: 94A15, 94A17, 94A24, 26D15.
ANTIOXIDANT ACTIVITY AND DETERMINATION OF TOTAL PHENOLICS OF NATURAL PRODUCTS FROM THE BRAZILIAN FLORA

INTRODUCTION: In the scientific field, several studies have been developed in order to find new antioxidant substances of plant origin. Free radicals play an important role in the biochemical/physiological reactions of the human body. However, if there is excessive production during pathophysiological processes or due to adverse environmental factors and antioxidants are not available in the medium, profound tissue damage can occur. METHODS: This article aimed to identify potential natural products with antioxidant action and with a high content of total phenolics. Seventeen native natural products were evaluated, in the antioxidant tests, the DPPH method was used and, for total phenolics, the Folin-Ciocalteau method was used. RESULTS AND DISCUSSION: The extracts that showed higher phenolic contents were Anadenanthera macrocarpa and Triplaris gardneriana, with values of 2266.84 ± 9.28 µmol g-1 and 2526.13 ± 476.90 µmol g-1 for antioxidants, and 563.04 ± 4.17 mg gallic acid g-1 and 414.82 ± 414.82 ± 3.57 mg gallic acid g-1 for phenolics. Therefore, this study contributed to help future works aimed at the development of products from the species studied.
Pseudodifferential equations, wave factorization, and related problems

We consider a model elliptic pseudodifferential equation in a special canonical domains of a multidimensional space. Using a special representation for an elliptic symbol, we give the formula for a general solution of such an equation and choose additional conditions under which this boundary value problem has a unique solution in appropriate Sobolev‐Slobodetskii spaces. Also, we introduce some transmutation operators that help us in constructing the solution.
Boosting resonant switched-capacitor voltage tripler

: This elaboration presents the concept of a unidirectional DC–DC switched-capacitor converter operating as a voltage tripler. The system consists of two resonant cells with switched capacitors and chokes. This proposed converter topology achieves low voltages on semiconductor switches (diodes and transistors) compared to the classic SC series-parallel converter or the boost topology. The output voltage on the capacitors is reduced in the proposed converter because it is divided into two series-connected capacitors with asymmetric distribution. The presented results describe the analytical description of the system operation and the analytical equation for semiconductor currents. A simulation and experimental results have been performed. The system eﬃciency and three voltage gain values were measured in the experimental setup. The eﬃciency measured was also compared with the analytical determination curve for loss analysis and further converter optimization.
INVESTOR SENTIMENT AND STOCK RETURNS: EVIDENCE IN MALAYSIA

The objective of the research is to investigate the role of investor sentiment in Malaysia’s stock returns. The state of investor rationality and efficiency of the stock market is debated in theoretical lenses of the behavioural finance paradigm. The behavioural factor, namely, closed-end fund discount, advance-decline ratio, trading volume/turnover, consumer sentiment index (CSI) and business condition index (BCI) that act as the sentiment proxies. These variables are utilized to analyse the relationship with stock returns by implementing a statistical method including Ordinary Least Square (OLS) regression model. The research findings are suggested consistently with theoretical perspectives on the view of behavioural finance and existing evidence on revealing the relationship between sentiment and stock market return index that is statistically significant. However, the risk proxies’ relationship with the stock market is heterogeneous that is in line with the view of the stock market in a complex state. In summary, this study offers important finance body of knowledge (academic), practice (investor) and policy implications through a new insight of theoretical and empirical evidence on the role of sentiment towards the stock market in Malaysia. Briefly, behavioural factors in particular sentiments can be taken into consideration instead only relying on a fundamental factor for stock investment decision making.
Quotients of orders in algebras obtained from skew polynomials and possible applications

We describe families of nonassociative finite unital rings that occur as quotients of natural nonassociative orders in generalized nonassociative cyclic division algebras over number fields. These natural orders have already been used to systematically construct fully diverse fast-decodable space-time block codes. We show how the quotients of natural orders can be employed for coset coding. Previous results by Oggier and Sethuraman involving quotients of orders in associative cyclic division algebras are obtained as special cases.
Approximation of the Meta-Analytic-Predictive Prior Distribution in the One-Way Random Effects Model with Unknown Variance

In order to use historical data in the design of sample surveys with a Bayesian approach, the information from the historical data must be expressed as a prior distribution. Then, the best prior distribution for the parameter of interest is a predictive distribution. The density function of the predictive distribution generally is not available in an analytical form. From the perspective of practical use, Schmidli et al. (2014) proposed an approximation for the predictive distribution using a mixture of conjugate prior distributions. Their method relies on random numbers drawn from the predictive distribution. However, if the population distribution includes a nuisance parameter, their method becomes impractical. We propose a new approximation method that does not rely on these simulated numbers. Our approximation instead minimizes the mean squared error between the exact Bayes estimator and the one corresponding to the approximated predictive distribution.
New Technologies and Jobs in Europe

We examine the link between labour market developments and new technologies such as artificial intelligence (AI) and software in 16 European countries over the period 2011-2019. Using data for occupations at the 3-digit level in Europe, we find that on average employment shares have increased in occupations more exposed to AI. This is particularly the case for occupations with a relatively higher proportion of younger and skilled workers. This evidence is in line with the Skill-Biased Technological Change theory. While there is heterogeneity across countries, very few countries show a decline in the employment shares of occupations more exposed to AI-enabled automation. Country heterogeneity for this result appears to be linked to the pace of technology diffusion and education, but also to the level of product market regulation (competition) and employment protection laws. In contrast to the findings for employment, we find little evidence for any correlation between wages and potential exposures to new technologies.