Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-band filter using composite microstrip/CPW structure

A novel and compact dual-band filter using a microstrip/coplanar waveguide (CPW) composite structure is proposed. At the bottom of the substrate material, two CPW open-circuited resonators are broadside-coupled to the top microstrip open-circuited stubs. The proposed filter was designed, fabricated and measured. The obtained frequency responses demonstrated that the filter has good dual-band property.
Covid 19 Küresel Salgın Sürecinde Kentsel Kamusal Alanlarda Güvenlik Algısının Değişimi

By the reason of pandemic precautions; the understanding of safety in public spaces has also changed. Precautions such as provision of social distance, use of masks, and ability to monitor people in terms of disease symptoms under necessary conditions have caused changes in the use of public space. This situation also revealed that urban spaces are not prepared for crises. In the Covid-19 period, the safety parameter, which is an invariable component of urban public space, should be evaluated with different criteria compared to the pre-pandemic period. This study aims to reveal the changing user perception and safety parameter in urban public space. In the first part of the study, the concept of safety is defined by examining the definitions of place, space and changing public space. In the second part, the research method and observation tools are explained. As case study area, the coastal park in the east of Mersin Marina en-trance, which is one of the most actively used areas with Covid-19 measures as well as before pandemic, is examined. In the last part, suggestions regarding safety parameter and concept of safety are presented based on user behaviour in urban-public spaces in the Covid-19 process.
Adaline neural networks for online extracting the direct, inverse and homopolar voltage components from a composite voltage

This work describes an improved Adaline neural networks method for online extracting the direct, inverse and homopolar voltage components from a composite voltage. A new voltage decomposition is thus proposed and developed. These skills are transferred to four Adalines by fixing their inputs. Adaline neural networks are used with a LMS learning process to compute the weights biases and thus to find out the amplitude and the phase of the direct, inverse and homopolar voltages of the electrical network. The learning allows an online adaptation to the changing parameters of the electrical network, e.g., nonlinear and time-varying loads. Compliant reference signals, i.e., sinusoidal and equilibrated voltages, are obtained from the proposed neural method, enhancing the harmonics compensations performance. A comparison with a conventional PLL is also addressed. Simulations and experiments are reported. decomposition of the three-phase voltages. Starting from the instantaneous values of the voltages and currents in phase components, d - q or α - β, it is possible to calculate the real and imaginary instantaneous powers and to decompose them in frequency harmonics. Based on the d - q transform, we introduce a new particular decomposition which will represent some kind of a priori knowledge of the electrical network and yield inputs to four Adalines. The LMS learning algorithm is then used to adapt and optimize the Adaline weights and thus enables to handle electrical networks with changing parameters, e.g., nonlinear and time-varying loads. This work is the prior step for online identifying and compensating harmonics in an APF scheme. More precisely, this compensating scheme will allow to identify the harmonics currents and thereafter to inject them in opposite phase in the low-voltage power systems via a control device. In the second section, direct voltage component extraction is reviewed (with the PLL for power systems), then extracting the direct, inverse and homopolar voltage components with Adaline neural networks is introduced (which represents the originality of the work). The Adaline algorithm is presented in the third section of this work. The simulation and experimental results are reported in the fourth section and show a significant improvement on harmonics compensation. Compared to a method based on a conventional PLL, the proposed neural method can ensure a rapid and efficient learning.
Semi‐supervised multiple empirical kernel learning with pseudo empirical loss and similarity regularization

Multiple empirical kernel learning (MEKL) is a scalable and efficient supervised algorithm based on labeled samples. However, there is still a huge amount of unlabeled samples in the real‐world application, which are not applicable for the supervised algorithm. To fully utilize the spatial distribution information of the unlabeled samples, this paper proposes a novel semi‐supervised multiple empirical kernel learning (SSMEKL). SSMEKL enables multiple empirical kernel learning to achieve better classification performance with a small number of labeled samples and a large number of unlabeled samples. First, SSMEKL uses the collaborative information of multiple kernels to provide a pseudo labels to some unlabeled samples in the optimization process of the model, and SSMEKL designs pseudo‐empirical loss to transform learning process of the unlabeled samples into supervised learning. Second, SSMEKL designs the similarity regularization for unlabeled samples to make full use of the spatial information of unlabeled samples. It is required that the output of unlabeled samples should be similar to the neighboring labeled samples to improve the classification performance of the model. The proposed SSMEKL can improve the performance of the classifier by using a small number of labeled samples and numerous unlabeled samples to improve the classification performance of MEKL. In the experiment, the results on four real‐world data sets and two multiview data sets validate the effectiveness and superiority of the proposed SSMEKL.
Ocean-science mission needs: real-time AUV data for command, control, and model inputs [West Florida

Predictive models for tides, hydrodynamics, and bio-optical properties affecting the visibility and buoyancy of coastal waters are needed to evaluate the safety of personnel and equipment engaged in maritime operations under potentially hazardous conditions. Predicted currents can be markedly different for two-layer systems affected by terrestrial runoff than for well-mixed conditions because the layering decouples the surface and bottom Ekman layers and rectifies the current response to oscillatory upwelling- and downwelling-favorable winds. Standard ocean models (e.g. Princeton Ocean Model) require initial and boundary data on the physical and optical properties of the multilayered water column to provide accurate simulations of heat budgets and circulation. Two observational systems are designed to measure vertically structured conditions on the West Florida Shelf (WFS): a tethered buoy network and an autonomous underwater vehicle (AUV). The AUV is described with a focus on the observational systems that challenge or limit the communications command and control network for various types of measurement programs. These include vertical oscillatory missions on shelf transects to observe the optical and hydrographic properties of the water column, and bottom-following missions for measuring the bottom albedo. Models of light propagation, absorption, and conversion to heat as well as determination of the buoyancy terms for physical models require these measurements.
Partisan Technocrats: How Leaders Matter in International Organizations

International organizations make policy decisions that affect the lives of people around the world. We argue that these decisions depend, in part, on the political ideology of the organization's chief executive. In this study, we investigate the influence of the leader of one of the most powerful international organizations: the Managing Director of the International Monetary Fund (IMF). We find that when the Managing Director is politically left of center, the IMF requires less labor market liberalization from borrowing countries in exchange for a loan. We also find evidence suggesting that the Managing Director's influence on labor-related loan conditions is independent of the Fund's most powerful members, including the United States. While Managing Directors rarely engage in overtly political behavior, they appear to act as “partisan technocrats” whose ideology influences international financial rescues and specifically the conditions attached to countries’ loans, which shape the distributive consequences of IMF lending.
Investigation of Health Behavior on Burnout Scores in Women Physicians who Self-Identify as Runners: A Cross-Sectional Survey Study

As the proportion of women in the physician workforce increases, burnout in this population warrants further investigation. Exercise is an often-proposed strategy to combat burnout. Evaluating physical activity across a cohort of women physicians can assess associations of health behaviors with burnout. Cross-sectional study of women attending physicians in the United States who are actively engaged in a social media group for runners. An electronic survey comprised of 60 questions covering demographics, health behaviors, and burnout was administered. A healthy lifestyle subgroup (HLS) was defined based on American Heart Association physical activity and nutrition recommendations. We determine the prevalence of burnout and investigate associations between health behavior factors and burnout. Of the 369 included surveys, most respondents were at least six years out from medical training (85.9%) and White (74.5%). Forty-two percent experienced burnout symptoms. Time exercising was significantly associated with fruit/vegetable consumption (P=.00002). There was no significant difference in burnout between the HLS compared to others (P = .37). This group of self-reported physically active women physicians was found to have a lower prevalence of burnout when compared to other women physicians. Exercise and nutrition may be protective against burnout in women physicians but deserve further investigation.
Utilização de Imagens no Domínio da Frequência Espacial e Redes Neurais Artificiais para Determinação de Propriedades Ópticas de Tecidos

As propriedades ópticas de tecidos biológicos podem ser utilizadas como parâmetros indicativos de alterações tanto morfológicas quanto fisiológicas nos tecidos. A técnica de imagens ópticas no domínio da frequência espacial (SFDI) vem apresentando grande potencial determinação dessas propriedades. Neste trabalho, investigamos a utilização de Redes Neurais Artificiais (RNA) para reconhecimento de padrões, na determinação das propriedades ópticas de tecidos, através dos coeficientes de absorção e espalhamento reduzido,  𝑎 e  𝑠′ , a partir de dados de refletância difusa fornecidos pela técnica SFDI. Empregou-se uma RNA do tipo feedforward com uma camada oculta e 50 neurônios, utilizando aprendizagem supervisionada por retropropagação de erros. O treinamento da rede foi realizado a partir de um conjunto de valores pré-determinados de refletância difusa e coeficientes de absorção pele; SFDI; propriedades ópticas. Abstract The optical properties of biological tissues can be employed as indicative parameters for morphological and physiological alterations. The technique of spatial frequency domain imaging (SFDI) has shown great potential in determining these properties. In this work, the use of Artificial Neural Networks (ANN) was investigated for pattern recognition in the determination of the optical properties of tissues, through the absorption and reduced scattering coefficients,  𝑎 and  𝑠′ , from diffuse reflectance data provided by SFDI. A feedforward ANN with one hidden layer and 50 neurons was employed, using supervised learning with error backpropagation. The network training was performed from a set of predetermined values of diffuse reflectance and absorption and scattering coefficients obtained from Monte Carlo simulations. Results show that the ANN can accurately determine the optical properties from diffuse reflectance data, providing values of  𝑎 and  𝑠′ with coefficient of determination R 2 of 0.98 and 0.97, respectively, relative to the true values, e showing average percentual errors of 2.6 and 4.9% for each coefficient. The RNA obtained was then employed, together with the SFDI technique, in an investigation to obtain images of skin regions of a patient who had a lesion. The results obtained point out to the potential of using artificial intelligence techniques combined
Electrical properties and detection methods for CMOS IC defects

CMOS failure modes and mechanisms and the test vector and parametric test requirements for the detection are reviewed. The CMOS stuck-open fault is discussed from a physical viewpoint, with results given from failure analysis of ICs having this failure mode. The results show that among functional, stuck-at, stuck-open, and I/sub DDQ/ test strategies, no single method guarantees detection of all types of CMOS defects. The I/sub DDQ/ test is the most sensitive and comprehensive, but can miss certain open-circuit defects and is a relatively slow measurement technique. The test-vector approach detects fewer of the CMOS defects, but can run at fast clock rates to detect certain open-circuit faults that may not be detectable by the I/sub DDQ/ test. Maximal CMOS IC defect detection involves a mixed-mode strategy of I/sub DDQ/ tests and vector stimulus/response tests. <<ETX>>
Creative analytics: Towards data‐inspired creative decisions

Organisations across many industries are increasing the use of evidence‐based approaches to decision‐making through adoption of business analytics. Creative processes and decisions are an area of organisational decision‐making which has traditionally been highly intuition‐based, and where professional culture and practices are often very different from the engineering disciplines from which data‐driven decision approaches originate. Through the case study of the analytics‐oriented transformation of creative decisions at Rovio, a leading game development company, this study seeks to understand how organisations can make their creative decision processes more evidence‐based, while retaining the best features of artistic intuition and human creativity. The case study highlights several issues that need to be delicately managed and balanced to effectively combine analytics and human creativity, and offers five principles for such “creative analytics”: (1) build shared analytics values but provide tailored BA support; (2) build hybrid teams; (3) balance commercial and creative goals; (4) encourage creative experimentation and learning; and (5) make data‐inspired, not data‐driven, creative decisions.
A Comparison of CustomersSatisfaction with Aerobics and Bodybuilding in Public and Private Gyms

The purpose of the present study is to compare the customerssatisfaction with aerobics and bodybuilding in public and private gyms in Kermanshah-Iran. It was descriptive- survey research. The statistical population were all female private and public customers in aerobics and bodybuilding gyms in Kermanshah. The study sample was 250 female athletes. In order to gather data, a researcher- made questionnaire with the reliability (α = 0.81) was administered. In order to analyze the data, we applied descriptive statistics and inferential statistics including Kolmogrov - Smirnov, t-independent and Friedman rank tests. Data analysis showed that customer satisfaction results between private and public aerobics and bodybuilding gyms for women were significantly different (p 0.05). Private gyms and public priorities in terms of customer satisfaction were satisfaction with trainers and gym personnel, satisfaction with the equipment and physical environment of the gyms, social satisfaction, and satisfaction with services and cultural facilities in the gym. Overall customer satisfaction in the private gyms was higher than public gyms.
Contact resistance study of high-copper alloys used in power automotive connectors

Abstract Contact resistance of the copper alloys used in automotive connectors was studied in the literature, but no study has been undertaken in order to optimize this resistance for the new high-copper alloys intended for power automotive connectors. This study was carried out in order to determine the changes in resistance for different loadings and contact geometries. A new generation of high-performance copper alloys was analysed. The used samples were U shaped with a segment containing a sphere and were subjected to insertion (sliding contact) and indentation (static contact) tests. A finite element simulation using the ANSYS code gave contact modellings with or without roughness; this roughness was measured with a profilometer. Numerical modelling of the contact surfaces when the roughness of the materials was taken into account led to results close to the experimental results especially in the case of the lower forces during the indentation test. On the other hand, a relation between the contact resistance and the contact force was established. These results could help in the choice of a material to provide a good compromise concerning both the electrical and the mechanical aspects for a power connector used for automotive industry.
Design centering by yield prediction

Design centering is an appropriate design tool for all types of electrical circuits to determine the nominal component values by considering the component tolerances. A new approach to design centering will be presented, which starts at the initial nominal values of the circuit parameters and improves these nominal values by maximizing the circuit yield step by step with the aid of a yield prediction formula. Using a variance prediction formula additionally, the yield maximization process can be established with a few iteration steps only, whereby a compromise between the yield improvement and the decrease in statistical certainty must be made in each step. A high-quality interactive optimization method is described which allows a quantitative problem diagnosis. The yield prediction formula is an analytical approximation based on the importance sampling relation. This relation can also be used to reduce the sample size of the necessary Monte Carlo analyses. Finally the efficiency of the presented algorithm will be demonstrated on a switched-capacitor filter.
TEM Pseudoelliptic-Function Bandstop Filters Using Noncommensurate Lines

A synthesis procedure for distributed bandstop filters that approximate an elliptic-function response is described. Existing tables of lumped constant elliptic-function filters are used together with an approximate transform that exchanges commensurate Foster sections for noncommensurate pairs of stubs or coupled lines. The method is usable for all bandwidths up to about 100 percent, providing that networks with a relative bandwidth of more than 50 percent are considered to be pseudo-low-pass.
A closed form solution of junction to substrate thermal resistance in semiconductor chips

The model presented in this work is based on an extension of the constant angle heat spreading, taking into account chip and substrate dimensions, and changing the spreading angle accordingly. This yields to closed form expressions accurate enough for most practical applications. Circular, square, and rectangular geometries have been analyzed and the results compared with Bessel and Fourier series-like solutions.
RANCANG BANGUN JARINGAN HOTSPOT PADA KAMPUS NIVERSITAS NUSANTARA MANADO MENGGUNAKAN ROUTER MIKROTIK

Jaringan internet sudahlah menjadi hal yang tidak asing di telinga kita. Internet sudahlah menjadi kebutuhan pokok bagi kita yang hidup di era komunikasi global. Kebutuhan akan adanya media komunikasi yang cepat dan handal telah dijawab lewat teknologi Internet. Penggunaan teknologi internet telah mewabah dan menjadi hal wajib dalam berbagai aspek kehidupan masyarakat. Misalnya, di bidang perbankan, perdagangan, keamanan, pemerintahan, pendidikan, dan berbagai aspek lainnya. Di bidang pendidikan, internet dibutuhkan untuk mengkomunikasikan informasi dari berbagai bidang ilmu pengetahuan yang ada di berbagai belahan bumi. Dengan internet, mahasiswa misalnya, bisa mengakses berbagai macam informasi mengenai bidang ilmu pengetahuan yang sedang ditekuninya secara aktual dan cepat. Tentunya hal ini, akan membantu proses belajar dari mahasiswa itu sendiri. Oleh karena itu, setiap kampus yang ada haruslah menyediakan fasilitas hotspot yang bisa diakses dari setiap laptop ataupun smartphone yang dimiliki mahasiswa. Dengan demikian, setiap mahasiswa yang ada, selama berada di kampus bisa memperoleh layanan internet guna mendukung proses pembelajaran. Yang tentunya dengan fasilitas internet ini, juga akan membantu para dosen yang ada dalam mencari dan menyiapkan materi perkuliahan. Dan untuk mengimplementasikan jaringan hotspot ini, maka akan digunakan router Mikrotik sebagai server utama jaringan hotspot.
Characterization of Virulence Function of Pseudomonas cichorii Avirulence Protein E1 (AvrE1) during Host Plant Infection

Pseudomonas cichorii secretes effectors that suppress defense mechanisms in host plants. However, the function of these effectors, including avirulence protein E1 (AvrE1), in the pathogenicity of P. cichorii, remains unexplored. In this study, to investigate the function of avrE1 in P. cichorii JBC1 (PcJBC1), we created an avrE1-deficient mutant (JBC1ΔavrE1) using CRISPR/Cas9. The disease severity caused by JBC1ΔavrE1 in tomato plants significantly decreased by reducing water soaking during early infection stage, as evidenced by the electrolyte leakage in infected leaves. The disease symptoms caused by JBC1ΔavrE1 in the cabbage midrib were light-brown spots compared to the dark-colored ones caused by PcJBC1, which indicates the role of AvrE1 in cell lysis. The avrE1-deficient mutant failed to elicit cell death in non-host tobacco plants. Disease severity and cell death caused by JBC1ΔavrE1 in host and non-host plants were restored through heterologous complementation with avrE1 from Pseudomonas syringae pv. tomato DC3000 (PstDC3000). Overall, our results indicate that avrE1 contributes to cell death during early infection, which consequently increases disease development in host plants. The roles of PcJBC1 AvrE1 in host cells remain to be elucidated.
Analysis of the associations between variables derived throughout velocity-based training device and jumping performances in youth soccer players: Multiple regression study

Background: It has been suggested that velocity-based training (VBT) improves real-life performance in sports, such as jumping, but studies rarely examined the associations between variables derived during VBT (VBT-variables) and jumping performances. Objective: The aim of this study was to investigate the associations between VBT-variables derived during deadlift exercise executed at different loads and anthropometric variables, and vertical and horizontal jump performance in young athletes. Methods: Seventeen youth soccer players (16-18 years old) were included. Predictors were body height, body mass, body fat percentage, and VBT-variables (force, power, and velocity) measured at different loads (45%, 55%, 65%, 75%, 85%, and 95%) of a one-repetition maximum deadlift (1RM). Criteria included tests of vertical and horizontal jumping performance. Results: The VBT-variables are more strongly correlated with horizontal jumps (Pearson's r up to .81) than vertical jumps (Pearson's r up to .75). The VBT-variables for the deadlift recorded at lower loads stronger correlated with jumping performance than the VBT-variables recorded at higher loads. Conclusions: Results of the study suggest that light-to-moderate loads (45%-65% of 1RM) maximize power output and are therefore more strongly related to jumping performance in youth athletes. Further intervention studies aimed at the improvement of jumping performances using the VBT are warranted.