Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Approach to Identifying Unknown Unknowns of Predictive Models

When predictive models are deployed in the real world, the confidence of a given prediction is often used as a signal of how much it should be trusted. It is therefore critical to identify instances for which the model is highly confident yet incorrect, i.e. the unknown unknowns. We describe a hybrid approach to identifying unknown unknowns that combines the previous crowdsourcing and algorithmic strategies, and addresses some of their weaknesses. In particular, we propose learning a set of interpretable decision rules to approximate how the model makes high confidence predictions. We devise a crowdsourcing task in which workers are presented with a rule, and challenged to generate an instance that “contradicts” it. A bandit algorithm is used to select the most promising rules to present to workers. Our method is evaluated by conducting a user study on Amazon Mechanical Turk. Experimental results on three datasets indicate that our approach discovers unknown unknowns more efficiently than the state-of-the-art.
Multiple Codebook-Based Non-Orthogonal Multiple Access

Observing that employing a single codebook (CB) per user transmission block in the conventional CB-based non-orthogonal multiple access (NOMA) schemes doesn’t exploit code and interference diversity and has limitations in some unfavorable channel conditions, this letter presents multiple CB-based NOMA (MC-NOMA) in which multiple CBs are employed by a user in a round robin manner. Performance of schemes such as sparse code multiple access (SCMA) and pattern division multiple access (PDMA) is improved by MC-NOMA without incurring any additional receiver complexity and loss in spectral efficiency. Furthermore, to fully exploit code and interference diversity for MC-NOMA, CBs assignment algorithm is presented.
The Benefits of Intervention: Birth Weights in Basle 1912-1920

To assess the impact of interventions on well-being during war time, we analyze data from the birth records at the university maternity hospital of Basle in the period 1912-1920. Birth weight of children from medium SEP families decreased during the crisis years 1918 and 1919, but not for low and high SEP families. A potential explanation is access to food: while high SEP families could compensate for high prices, low SEP families received support, for which medium SEP families were not eligible.
The Impact of System Noise in Polarimetric SAR Imagery on Oil Spill Observations

The effects of both system additive and multiplicative noise on the X-, C-, and L-band synthetic aperture radar (SAR) data covering oil slicks are examined. Prior studies have attempted to characterize such oil slicks, primarily through analysis of polarimetric SAR data. In this article, we factor in system noise that is added to the backscattered signal, introducing artifacts that can easily be confused with random and volume scattering. This confusion occurs when additive and/or multiplicative system noise dominates the measured backscattered signal. Polarimetric features used in this article are shown to be affected by both additive and multiplicative system noise, some more than others. This article highlights the importance of considering specifically multiplicative noise in the estimation of the signal-to-noise ratio (SNR). The SNR based on additive noise should at least be above 10 dB and the SNR involving both additive and multiplicative noise should at least be above 0 dB. The SNR from TerraSAR-X (TS-X) and Radarsat-2 (RS-2) is below 0 dB for the majority of the oil slick pixels when considering both the additive and multiplicative noise, rendering these data unsuitable for any analysis of the scattering properties and characterization. These results are in contrast to the reduced impact of noise on oil slicks detected by the L-band UAVSAR system. In particular, we find that there is no need to invoke exotic scattering mechanisms to explain the characteristics of the data. We also recommend a noise subtraction for any polarimetric scattering analysis.
A COMPACT FLEXIBLE PRINTED MONOPOLE ANTENNA WITH EMBEDDED PERIODIC H-SHAPED SLOTS FOR WLAN APPLICATIONS

—In this paper, a compact printed monopole antenna with periodic H-shaped slots for WLAN application is proposed, designed, and fabricated with standard ﬂexible printed circuit board process. By cutting four H-shaped slots in the radiation patch of the printed monopole antenna, the resonant frequency of the monopole antenna can be reduced; therefore, a compact antenna is realized. The radiator size of the antenna is 0 . 07 λ g × 0 . 19 λ g , which is much smaller than that of a traditional printed monopole antenna. By utilizing electromagnetic simulation software CST, the antenna is simulated and optimized. Moreover, the performance of the proposed antenna is discussed taking into consideration the possible eﬀects of deformations due to the ﬂexibility of the substrate. A sample antenna is manufactured and measured to prove the predicted performance of our proposed antenna. The measured results agree well with the simulations. Hence, the proposed method in this paper is a promising candidate for the design of compact antennas.
Efficient Broadband Vibration Energy Harvesting Using Multiple Piezoelectric Bimorphs

This paper presents complete nonlinear electromechanical models for energy harvesting devices consisting of multiple piezoelectric bimorphs (PBs) connected in parallel and series, for the first time. The proposed model is verified against available experimental results for a specific case. The piezoelectric and beam constitutive equations and different circuit equations are utilized to derive the complete nonlinear models for series and parallel connections of the PBs as well as those of piezoelectric layers in each bimorph, i.e., four nonlinear models in total. A multi-modal Galerkin approach is used to discretize these nonlinear electromechanical models. The resultant high-dimensional set of equations is solved utilizing a highly optimized and efficient numerical continuation code. Examining the system behavior shows that the optimum load resistance for an energy harvester array of 4 PBs connected in parallel is almost 4% of that for the case with PBs connected in series. It is shown an energy harvesting array of 8 PBs could reach a bandwidth of 14 Hz in low frequency range, i.e., 20–34 Hz. Compared with an energy harvester with 1 PB, it is shown that the bandwidth can be increased by more than 300% using 4 PBs and by more than 500% using 8 PBs. Additionally, the drawbacks of a multi-PB energy harvesting device are identified and design enhancements are proposed to improve the efficiency of the device.
Autonomous Underwater Vehicles: Localization, Navigation, and Communication for Collaborative Missions

Development of Autonomous Underwater Vehicles (AUVs) has permitted the automatization of many tasks originally achieved with manned vehicles in underwater environments. Teams of AUVs designed to work within a common mission are opening the possibilities for new and more complex applications. In underwater environments, communication, localization, and navigation of AUVs are considered challenges due to the impossibility of relying on radio communications and global positioning systems. For a long time, acoustic systems have been the main approach for solving these challenges. However, they present their own shortcomings, which are more relevant for AUV teams. As a result, researchers have explored different alternatives. To summarize and analyze these alternatives, a review of the literature is presented in this paper. Finally, a summary of collaborative AUV teams and missions is also included, with the aim of analyzing their applicability, advantages, and limitations.
Regularized Deep Transfer Learning: When CNN Meets kNN

In this brief, we propose a regularized deep transfer learning architecture composed of a softmax classifier and a <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>-nearest neighbor (<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NN) classifier. We aim to generalize the softmax classifier possibly well under the regularization effect of the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NN classifier. That is, given a training sample, the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NN classifier assigns a soft label vector according to its distance to the center of each class. The working mechanism of the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NN classifier is attributed to both the source and target domains. On the one hand, it gradually becomes stronger by backpropagating the cross-entropy classification loss on the source images. On the other hand, for target data, we enforce to minimize the discrepancy between the label vectors produced by the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NN classifier and the softmax classifier. Using the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NN classifier, we are able to reduce the intra-class variations on the source domain and meanwhile pull close the source and target feature distributions, which can better bound the expected error of target domain. In experiment, we demonstrate that our method compares favorably with the state-of-the-arts on benchmarks.
Depression, Anxiety and Quality of Life among Chronic Low Back-leg Pain Patients with or without Neuropathic Pain

Aims: To investigate depression, anxiety and quality of life among chronic low back-leg pain patients with or without neuropathic pain. Place and Duration of Study: Ankara Numune Education and Research Hospital Department of Physical Medicine and Rehabilitation Polyclinic, between October 2012 and June 2013. Methodology: One hundred and one patients with chronic low back and leg pain were enrolled in the study. This study is a cross-sectional study. The severity of low back and leg pain was evaluated by visual analogue scale (VAS). The DN4 (Douleur Neuropathique en 4 Questions) and LANSS (Leeds Assessment of Neuropathic Symptoms and Signs) scales were used in order to evaluate the neuropathic pain. Existence of depression was evaluated by the Hamilton Depression Rating Scale (HAM-D) and anxiety was assessed by Hamilton Anxiety Rating Scale (HAM-A). The quality of life was questioned by Short Form-36 (SF-36). Results: Neuropathic pain was detected in 65.3% by DN4 and 40.6% by LANSS among all patients. According to HAM-D results, 22.7% of the patients had depression and according to HAM-A results, 8.9% of the patients had anxiety. While frequency of depression was statistically Original Research Article Uzun et al.; BJPR, 13(5): 1-8, 2016; Article no.BJPR. 28762 2 significantly higher in patients with neuropathic pain according to LANSS (p<0,05), the frequency of anxiety was similar between groups. Although depression and anxiety was more common among patients with neuropathic pain according to DN4, there was no statistically significant difference between chronic low back-leg pain patients with or without neuropathic pain. The median SF-36 mental score was significantly lower in patients with NP according to LANSS (p<0.05). Although the median SF-36 scores (mental, physical) were higher in patients with NP according to DN4, there was no significant difference between groups (respectively p>0.05, p>0.05). Conclusion: Patients with chronic low back and leg pain should also be questioned in terms of neuropathic symtoms and the conservative treatment should be arranged in this direction. Thus concomitant depression and anxiety would decrease, and the quality of life would increase.
CHEMICAL AND MECHANICAL ADAPTATIONS OF THE RESPIRATORY SYSTEM AT REST AND DURING EXERCISE IN HEALTHY HUMAN PREGNANCY: IMPLICATIONS FOR RESPIRATORY SENSATION

Human pregnancy is characterized by significant increases in central ventilatory drive and perceived respiratory discomfort (breathlessness). The physiological mechanisms of hyperventilation and breathlessness in pregnancy remain unknown and largely understudied. Objective: The main purpose of this research was to elucidate the mechanisms of maternal hyperventilation, and to systematically examine the contribution of alterations in central ventilatory drive, static/dynamic respiratory mechanics and their interaction with respect to the intensity of perceived breathlessness during exercise in pregnancy. General Methods: Experiments were conducted between 34-38 wks gestation and again 4-5 months post-partum in a total of 35 healthy, young women. A comprehensive mathematical model of ventilatory control was used to examine the role of alterations in wakefulness and central chemoreflex drives to breathe, acid-base balance and female sex hormones in maternal hyperventilation. The effects of pregnancy on detailed ventilatory (breathing pattern, airway function, operating lung volumes, esophageal pressure-derived indices of respiratory mechanics) and perceptual (breathing and leg discomfort) responses to incremental cycle exercise to the limits of tolerance were also examined. Results: Maternal hyperventilation resulted from a complex interaction between alterations in arterial and central acid-base balance and other factors that directly affect ventilation, including increased wakefulness and central chemoreflex drives to breathe, increased metabolism and decreased cerebral blood flow. Mechanical adaptations of the respiratory system, including recruitment of resting inspiratory capacity and reduced airway resistance, accommodated the increased demand for tidal volume expansion during exercise in pregnancy, while preserving effort-displacement and breathlessness-
A Simple Phase-Shift Modulation Using Parabolic Carrier for Dual Active Bridge DC–DC Converter

The power transfer of a dual active bridge (DAB) dc–dc converter is not linearly proportional to the phase shift between the two active bridges. When the DAB converter controller receives the power reference, the phase shift needs to be obtained by either solving a quadratic equation online or looking up from a table. The online calculation method is computationally inefficient. The lookup table method has only limited operating points. In addition, when using interpolation to find missing operating points from the table, the control accuracy will be reduced. This letter proposes a simple phase-shift modulation using a parabolic carrier. The proposed method converts the power command into phase shift by modulation. Therefore, the solving of the quadratic equation can be eliminated. The Verilog results are provided to verify the proposed parabolic carrier. A case study of DAB with sinusoidal ripple current charging concept is provided to demonstrate the advantage of the proposed method.
Low Order Model for Transonic Afterbody Aerodynamic Characteristics

A key aspect in the preliminary design of new combat aircraft is the prediction of the afterbody and exhaust system aerodynamic drag. To meet the various operating conditions requirements for a multi-role vehicle the afterbody typically includes a variable geometry. Within the preliminary design context, this makes the aerodynamic performance prediction a difficult challenge. This research investigates reduced order models for prediction of the aerodynamic performance of axisymmetric transonic afterbody and nozzle systems for a range of aerodynamic conditions and geometric degrees of freedom. The aerodynamic performance metric of interest is afterbody drag coefficient (C D ). Two reduced order models are investigated: artificial neural network and Gaussian process. The geometric variables include boattail closing angle, nozzle throat to exit area ratio and afterbody mean angle and the aerodynamic parameters are free-stream Mach number and nozzle pressure ratio. The results show that these types of reduced order models can be used for preliminary design aerodynamic performance prediction. The Gaussian process C D prediction is less accurate compared to the artificial neural network with the latter giving a prediction uncertainty of approximately ±0.01 in C D with a 2 σ confidence level. The Gaussian process prediction uncertainty is approximately ±0.013 C D .
Prediction of Change Management Through the Use of Information Technology Components in the Ministry of Sports and Youth of the Islamic Republic of Iran

CITE: Ashraf Ganjoei, Yarmohamadi, Zarei, Prediction of Change Management Through the Use of Information Technology Components in the Ministry of Sports and Youth of the Islamic Republic of Iran, Research in sport management & motor behavior, 2020: 9(18):92-110 ABSTRACT The purpose of this study is to predict the management of change through the use of information technology components in the Ministry of Sports and Youth of the Islamic Republic of Iran. To collect data, a questionnaire was used to survey the acceptance and use of information technology in the workplace (Davis, 1989) in four sections: perceived usefulness with 6 questions, perceptual ease with 6 questions, attitude towards the use of information technology with 5 questions, and The tendency to use information technology with 4 questions and a total of 21 questions of five values (Likert number 1 to 5, too many) were used and the AdCaracy FAQ changed the management to assess the extent and the extent to which employees were exposed to changes in the workplace to measure The components of knowledge, desire, knowledge, ability, and reinforcement (Likert Five Value Questionnaire). The questionnaire from the translated translated article is a research article to investigate the extent and staff resistance to change (Boehne, 2012). It is worth mentioning that the questionnaire is a super standard and international, and with the confirmation of professors, Is. Its reliability has been approved and certified at an international level of 96%. The methodology of this research is descriptive-survey. The results of the research were descriptive and inferential statistics such as Kalmogorov-Smirnov (to determine the normality of the data), single-sample t-test (to determine the status of the main variables), Pearson correlation coefficient (to determine the relationships between variables), multiple regression test (forward direction Nasal variables) were analyzed using spss software. The results showed that there is a significant relationship between "change management" and "application of information technology". Also, there is a significant positive relationship between "perceived usefulness", "perceived ease", "attitude toward application" and "tendency to use" with "change management" (p <0.05). , So it can be deduced that change management can be predicted through the IT component. In this research, change management is considered as a criterion variable and is predicted through the application of information technology components. 1. Farideh Ashraf Ganjoei, (Ph.D) Islamic Azad University, Central Tehran Branch, Iran
Social Capital and Physical Activity Level in an Urban Adult Population

ABSTRACT Background: Despite several studies on the concept of social capital in relation to health during the last two decades, the majority of these works have been conducted in developed countries. Purposes: This study examines the correlation between domains of social capital (reciprocity, trust, and social network) and physical activity level in an Iranian adult population. In addition, the study explores to find whether this relation is affected by socioeconomic status. Method: A total of 2000 questionnaires were distributed among adults living in 12 neighborhoods of Bandar Abbas city, Iran. Of this population, 1828 qualified questionnaires were utilized for further analysis. Results: High level of physical inactivity (62.3%) was reported by the participants. Discussion: Norms of reciprocity and neighborhood trust associated with the higher physical activity level among men and women. However, social network contributed to a higher level of physical activity among women group. The study indicated the correlation of socioeconomic variables with social capital indicators and physical activity level. Translation to Health Education Practice: Findings suggest that programming efforts and research should focus on increasing organized activities that support neighborhood participation and social activity to promote social interaction and trust among residents. A AJHE Self-Study quiz is online for this article via the SHAPE America Online Institute (SAOI) http://portal.shapeamerica. org/trn-Webinars
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration

Generative Adversarial Networks (GANs) is a powerful family of models that learn an underlying distribution to generate synthetic data. Many existing studies of GANs focus on improving the realness of the generated image data for visual applications, and few of them concern about improving the quality of the generated data for training other classifiers -- a task known as the model compatibility problem. As a consequence, existing GANs often prefer generating `easier' synthetic data that are far from the boundaries of the classifiers, and refrain from generating near-boundary data, which are known to play an important roles in training the classifiers. To improve GAN in terms of model compatibility, we propose Boundary-Calibration GANs (BCGANs), which leverage the boundary information from a set of pre-trained classifiers using the original data. In particular, we introduce an auxiliary Boundary-Calibration loss (BC-loss) into the generator of GAN to match the statistics between the posterior distributions of original data and generated data with respect to the boundaries of the pre-trained classifiers. The BC-loss is provably unbiased and can be easily coupled with different GAN variants to improve their model compatibility. Experimental results demonstrate that BCGANs not only generate realistic images like original GANs but also achieves superior model compatibility than the original GANs.
A New High Precision Linear Displacement Sensor Based on Single Light Field Orthogonal Modulation

This paper present a single light field orthogonal modulation displacement measurement method which is based on time and space modulation technology. This method uses an alternating light intensity modulation in the time domain and modulation of four sinusoidal light-transmitting surfaces in the spatial domain to synthesize a traveling wave signal. The displacement was accurately reflected in the phase shift of the traveling wave signal, which could be measured by the time difference. A prototype with a measuring range of 500 mm and a pitch of 0.6 mm was fabricated to evaluate the proposed method. Combined with the measurement mechanism, the measurement errors caused by the spatial modulation were analyzed in detail. To reduce those primary periodic errors, we proposed an optimization structure of continuous cosinusoidal transmitting surfaces and demonstrated the effectiveness of this method by simulations and experiments. The experimental results indicate that the short period measurement accuracy reached ±0.29 $\mu \text{m}$ with 1 nm resolution within one period of 0.6 mm, which means that the accuracy in one period (0.6 mm) exceeded 0.1%. Furthermore, the original measurement accuracy of the full range of 500 mm was ±1.3 $\mu \text{m}$ , the error showed great regularity, and the better performance of the sensor could be obtained by digital calibration for the measurement data or improvement in the structure. Therefore, compared with the traditional measurement methods, the sensor described in this paper can achieve high-precision measurement with a low cost of manufacture.
Mechanisms of thrombogenesis in atrial fibrillation.

XII DECLARATION.XV ACKNOWLEDGEMENTS.XVI PUBLICATIONS AND COMMUNICATIONS TO LEARNED SOCIETIES.XVIII PRIZES AND AWARDS DURING CANDIDATURE.XXIV CHAPTER ONE LITERATURE REVIEW 1.