Miracle-dz/UniFAR-FTUs huggingface dataset:
Drag force on a flat plate in cavitating flows

Drag force on a flat plate in cavitating flows The present study focuses on the simulation of two dimensional unsteady cavitating flows. For simulation of unsteady behaviors of cavitation which have practical applications, the development of unsteady PISO algorithm based on the non-conservative approach is utilized. For multi-phase simulation, single-fluid Navier—Stokes equations, along with the volume fraction transport equation, are employed. The bubble dynamics model is utilized to simulate phase change between vapor and liquid phases of the water. Unsteady simulation of cavitation around NACA66(MOD) and supercavitation around a flat plate normal to flow direction are performed to clarify accuracy of presented model. Numerical results and comparisons with experimental data are provided. The accuracy is good, and it is possible to apply this method to more complex shapes.
Tunable arbitrary N-port CRLH infinite-wavelength series power divider

A novel composite right-/left-handed (CRLH) transmission line series power divider with an arbitrary and tunable number of output ports is proposed. This device operates at the CRLH infinite-wavelength frequency for equi-magnitude/phase power division and in the travelling-wave (as opposed to resonant) mode for frequency independence of the number of output ports. Owing to the infinite wavelength regime, the location of the output ports can be chosen arbitrarily. The proposed power divider is implemented in a shielded structure and hence is immune to leaky-wave radiation loss. In addition, its input impedance can be tuned to accommodate an arbitrary number of output ports by using a simple inductor and varactor-based L matching network. By reciprocity, this divider may also be used as a combiner.
Single current sensor technique in the DC-link of three-phase PWM-VS inverters. A review and the ultimate solution

This paper proposes an ultimate solution for reconstruction of three phase-currents in a PWM-voltage source inverter by one current sensor in the DC-link, and it gives a review of existing methods in literature and patents. The solution offers fully protection of the inverter including shoot-through of the DC-link, short-circuit of the output phases and earth faults with both low and high impedance. A special configuration in the DC-link can give such features. At the same time a new method to sample the DC-link current is proposed which both can eliminate disturbances from cables between an inverter and an induction motor, and it offers a true simultaneous sample value of all three phase-currents in the center of a switching period. The two methods are implemented in an experimental setup, and test results show that full protection is achieved and the three phase-currents are reconstructed precisely in the whole operating area.
Distribution of PAR in DMT systems

Central limit theorem, modern extreme value theory and the theory that the discrete multitone (DMT) signal converges weakly to a Gaussian random process are employed to derive perfect approximations of peak-to-average envelope power ratio (PAR) distributions of discrete-time and continuous-time DMT signals. Analysis and simulation results show that the PAR problem of DMT is more deteriorative than that of complex-valued OFDM signals.
Variable dispersion compensator using a VIPA with an extended bandwidth

We achieved variable dispersion compensator using a Virtually Imaged Phased Array (VIPA) with a wide pass band width by employing a high refractive index material to the plate. The channel spacing of the device is 100 GHz, and the extended pass band width is sufficient for 40-Gbit/s signals. (2 pages)
Security Architecture in Gaia

Ubiquitous computing promotes physical spaces with hundreds of computational devices extending the user''s view of the computational environment beyond the physical limitations of a traditional distributed system. Gaia OS is a middleware operating system that makes the realization of such spaces a possibility. In any such environment Security and Privacy are primary concerns and mechanisms to solve them have to be built into the very core of the system so that their deployment is acceptable and feasible. In this paper we describe a security architecture for Gaia OS and Active Spaces. Our architecture provides dynamism and flexibility to manage the security concerns in such a computing systems.
Instrumentation and methodology for revision of European flicker threshold

The European standard CENELEC EN 50160 establishes that the severity of flicker caused by voltage fluctuations, under normal operating conditions, will not exceed the long term severity Plt=1 during 95% of the time in one week. This threshold was originally established considering that a lamp with tungsten filament of 60 W and 240 V, produces a flicker perceivable by 50% of the population when it is supplied with a voltage that verifies Plt=1. This work makes an analysis of this threshold, establishing as hypothesis the fact that incandescent lamps have little use nowadays, specially in industrial and commercial environments. In order to make a revision of the current thresholds, we have proposed an electro-optical equipment and the associated methodology. The device simulates the behavior of the eye plus human brain set, avoiding large clinical experiments. A methodology is also proposed in order to characterize the perceptibility threshold of a generic lamp. Finally, the proposed instrumentation and methodology is applied to two types of lamps: incandescent and fluorescent.
Optimal Control Combining Emulation and Imitation to Acquire Physical Assistance Skills

This paper studies exploiting action-level learning (imitation) in the optimal control problem context. Cost functions defined by the optimal control methods are similar to the goal-level learning (emulation) in animals. However, imitating the robot's or others' (e.g. human's) previous experiences (demonstrations) could help the system to improve its performances. We propose to use demonstrations more efficiently by predicting an initialization for the optimal control problems (OCPs) and adding an imitation term to the cost functions. While the predicted initial guess initializes the OCPs close to their local optima, the imitation term guides the optimization, resulting in a faster convergence rate. We test our algorithm in a physical assistive task where a robot should help a human perform a sit-to-stand (STS) task. We define this task as two optimal control problems. The first OCP predicts the human's desired assistance and the other one controls the robot. We have tested our method on different experiments with different conditions for the human in which the robot should quickly solve the two optimization problems exploiting some demonstrations of how it can perform the task. Our proposed method reduced the number of iterations by more than 90% and 70% for the human assistance prediction and the robot controller, respectively, compared to the standard problem which does not take the demonstrations into account.
Non-linear Vibration and Dynamic Characteristic of Fish-like Robot Controlled by GMM Actuator

The swimming mechanism of the underwater fish-like robot, which is controlled by the giant magnetostrictive material actuator, is studied with the aid of the non-linear vibration method. A mechanics model of the robot is presented based on the relationship between the driving force and frequencies, which is controlled by external magnetic fields. The numerical results show that steady and unsteady solution of the project accord with the dynamic characteristics of tuna and pike fish, respectively.
Optimal power control for smart homes

Abstract This paper depicts a formulation of the global home electricity management problem, which consists in adjusting the electric energy consumption to the cost and availability variations of the power supply. The available flexibilities of the services to inhabitants are used to compute optimal plans for appliances control. Two optimization criteria are addressed: the user's comfort and the economic cost. A global multi-layer solving approach is depicted that includes first the computation of consumption/production coordination plans and then the dynamic matching to the actual consumption/production data. The paper focuses on the computation of the anticipative plan through a MILP formulation of the energy management problem. Application examples are given.
Discrimination of volcano activity and mountain-associated waves using infrasonic data and a backpropagation neural network

An integral part of the Comprehensive Nuclear Test Ban Treaty monitoring is an international infrasonic monitoring network that is capable of detecting and verifying nuclear explosions. Reliable detection of such events must be made from data that may contain other sources of infrasonic phenomena. Infrasonic waves can also result from volcanic eruptions, mountain associated waves, auroral waves, earthquakes, meteors, avalanches, severe weather, quarry blasting, high-speed aircraft, gravity waves, and microbaroms. This paper shows that a feedforward multi-layer neural network discriminator, trained by backpropagation, is capable of distinguishing between two unique infrasonic events recorded from single station recordings with a relatively high degree of accuracy. The two types of infrasonic events used in this study are volcanic eruptions and a set of mountain associated waves recorded at Windless Bight, Antarctica. An important element for the successful classification of infrasonic events is the preprocessing techniques used to form a set of feature vectors that can be used to train and test the neural network. The preprocessing steps used in our analysis for the infrasonic data are similar to those techniques used in speech processing, specifically speech recognition. From the raw time-domain infrasonic data, a set of mel-frequency cepstral coefficients and their associated derivatives for each signal are used to form, a set of feature vectors. These feature vectors contain the pertinent characteristics of the data that can be used to classify the events of interest as opposed to using the raw data. A linear analysis was first performed on the feature vector space to determine the best combination of mel-frequency cepstral coefficients and derivatives. Then several simulations were run to distinguish between two different volcanic events, and mountain associated waves versus volcanic events, using their infrasonic characteristics.
Charge-plasma-based super-steep negative capacitance junctionless tunnel field effect transistor: design and performance

A double-gate charge-plasma-based super-steep negative capacitance junctionless tunnel field effect transistor (NC-JLTFET) using a ferroelectric gate stack is proposed. Structurally, the NC-JLTFET consists of a heavily doped n-type silicon (Si) channel with two distinctive gates (control gate and fixed source gate). The fixed source gate accounts for the charge-plasma (hole plasma) formation which results in surrogate p-type doping by using work-function engineering. It induces a uniform p-region on the source side on the n-type doped Si film having a thickness less than the Debye length (L D). The key attribute of the NC-JLTFET is the ferroelectric gate stack which is employed as a control gate resulting in NC behaviour due to positive feedback among the electric dipoles in the ferroelectric material. The NC-JLTFET endeavours to achieve a super-steep sub-threshold slope, a paramount boost in drive current and a substantial enhancement in peak transconductance (g m) than the JLTFET. Meanwhile, it embraces the inherent advantages of the charge-plasma junctionless structure. Thus, it avails itself of a simple fabrication process flow and high immunity against process variations and random dopant fluctuations.
Agency in Hierarchies: Middle Managers and Performance Evaluations

This paper studies the optimal joint design of incentives and performance rating scales in a principal-manager-worker hierarchy. The principal wants to motivate the worker to exert unobservable effort at the minimum feasible cost. Given the worker’s effort, two signals are realized: public and verifiable output and a private non-verifiable signal known only to the manager. The principal may try to elicit the manager’s private information by requiring her to evaluate the worker’s performance. Payments may depend on output and the manager’s evaluation. I show that the principal can achieve no more than what is feasible with a binary rating scale. I also identify scenarios where subjective evaluations are valuable (non-valuable), reduced transparency is advantageous, and forced ranking outperforms individual evaluations.
MACHINE LEARNING AND CNN BASED DEEP LEARNING APPROACHES FOR AUTOMATED FLORAL DIVERSITY IDENTIFICATION OF THE WESTERN GHATS REGION

The conservation of plant biodiversity is primary, as the current rate at which plant species are depleting is alarming. Species conservation requires that one has a thorough knowledge of the species accompanied by the identification skills acquired by intense training and years of practice and involvement. On the other hand, advancement in computer vision has helped in automated species identification with promising results. This paper has discussed creating a dataset with 95 rare and endangered plant species of the Western Ghats region. The images of 95 plant species from western ghats were collected to create a dataset of images. The paper discusses the application of image processing techniques. First, pre-processing techniques like Noise reduction using simple thresholding techniques and Otsu's binarization techniques and closing morphological operation to address the damaged leaves in the dataset. The shape, color, and texture features that are retrieved from the leaves for identification reasons are then explored. We used typical machine learning algorithms to achieve varying levels of accuracy. In the second phase of the experimentation, the images are subject to the data augmentation process. The CNN model architecture is developed with a layer of fully connected artificial neurons to identify the plant species. The Artificial neural networks that act as autonomous human brains are trained to identify the plant species from the dataset. A neural network model is constructed with optimized parameters. The experimentation results demonstrate the accuracy of 84.12% in testing accuracy and 99.74% in training accuracy.
Evaluating Graduate Recruitment Programme in Malawian Banking Industry

Graduate Recruitment Programme is not receiving substantial attention in the Malawian Banking Sector. There are fragmented programmes across the industry with most banks lacking initiatives to recruit and train graduates from universities as means of building up future management team with common goals and long-term shared vision. Global banking industry is becoming more complex in view of the advent of numerous financial instruments which are integral part of the modern banking system. Experience alone is no longer an option for one to ascend to senior management position in the global banking perspective. Right qualifications could greatly assist the banking work force of the twenty-first century in Malawi. There could be tangible reasons affecting success of the Graduate Recruitment Programmes in Malawi. The benefits forgone would however be far too greater in the long run. Malawian banks should prioritise Graduate Recruitment Programme to ensure graduates are adequately trained to undertake strategic objectives with due competency while being committed to the organisation and high quality services to customers. The Banking sector should design Graduate Recruitment Programme with strategic focus while assisting the recruits to have an understanding of operational matters. Appropriate support and mentorship can provide an auspicious training environment for the recruits and assist them develop to their full capabilities. Malawian banking sector should take advantage of US$41 million funding from African Development Bank to improve employment prospects of graduates in Malawi.
Multimodality During Fixation – Part II: Evidence for Multimodality in Spatial Precision-Related Distributions and Impact on Precision Estimates

This paper is a follow-on to our earlier paper (7), which focused on the multimodality of angular offsets. This paper applies the same analysis to the measurement of spatial precision. Following the literature, we refer these measurements as estimates of device precision, but, in fact, subject characteristics clearly affect the measurements. One typical measure of the spatial precision of an eye-tracking device is the standard deviation (SD) of the position signals (horizontal and vertical) during a fixation. The SD is a highly interpretable measure of spread if the underlying error distribution is unimodal and normal. However, in the context of an underlying multimodal distribution, the SD is less interpretable. We will present evidence that the majority of such distributions are multimodal (68-70% strongly multimodal). Only 21-23% of position distributions were unimodal. We present an alternative method for measuring precision that is appropriate for both unimodal and multimodal distributions. This alternative method produces precision estimates that are substantially smaller than classic measures. We present illustrations of both unimodality and multimodality with either drift or a microsaccade present during fixation. At present, these observations apply only to the EyeLink 1000, and the subjects evaluated herein.
The small-secreted cysteine-rich protein CyrA is a virulence factor participating in the attack of Caenorhabditis elegans by Duddingtonia flagrans

Nematode-trapping fungi (NTF) are a diverse and intriguing group of fungi that live saprotrophically but can switch to a predatory lifestyle when starving and in the presence of nematodes. NTF like Arthrobotrys oligospora or Duddingtonia flagrans produce adhesive trapping networks to catch and immobilize nematodes. After penetration of the cuticle, hyphae grow and develop inside the worm and secrete large amounts of hydrolytic enzymes for digestion. In many microbial pathogenic interactions small-secreted proteins (SSPs) are used to manipulate the host. The genome of D. flagrans encodes more than 100 of such putative SSPs one of which is the cysteine-rich protein CyrA. We have chosen this gene for further analysis because it is only found in NTF and appeared to be upregulated during the interaction. We show that the cyrA gene was transcriptionally induced in trap cells, and the protein accumulated at the inner rim of the hyphal ring before Caenorhabditis elegans capture. After worm penetration, the protein appeared at the fungal infection bulb, where it is likely to be secreted with the help of the exocyst complex. A cyrA-deletion strain was less virulent, and the time from worm capture to paralysis was extended. Heterologous expression of CyrA in C. elegans reduced its lifespan. CyrA accumulated in C. elegans in coelomocytes where the protein possibly is inactivated. This is the first example that SSPs may be important in predatory microbial interactions.
Phosphorylation of eukaryotic initiation factor eIFiso4E enhances the binding rates to VPg of turnip mosaic virus

Binding of phosphorylated eIFiso4E with viral genome-linked protein (VPg) of turnip mosaic virus was examined by stopped-flow, fluorescence, circular dichroism (CD) spectroscopy, and molecular docking analysis. Phosphorylation of eIFiso4E increased (4-fold) the binding rates as compared to unphosphorylated eIFiso4E with VPg. Stopped-flow kinetic studies of phosphorylated eIFiso4E with VPg showed a concentration-independent conformational change. The dissociation rate was about 3-fold slower for eIFiso4E∙VPg complex upon phosphorylation. Phosphorylation enhanced the association rates and lowered the dissociation rates for the eIFiso4E∙VPg binding, with having higher preferential binding to eIFiso4Ep. Binding rates for the interaction of eIFiso4Ep with VPg increased (6-fold) with an increase in temperature, 278 K to 298 K. The activation energies for binding of eIFiso4Ep and eIFiso4E with VPg were 37.2 ± 2.8 and 52.6 ± 3.6 kJ/mol, respectively. Phosphorylation decreased the activation energy for the binding of eIFiso4E to VPg. The reduced energy barrier suggests more stable platform for eIFiso4Ep∙VPg initiation complex formation, which was further supported by molecular docking analysis. Moreover, far-UV CD studies revealed that VPg formed complex with eIFiso4Ep with substantial change in the secondary structure. These results suggested that phosphorylation, not only reduced the energy barrier and dissociation rate but also enhanced binding rate, and an overall conformational change, which provides a more stable platform for efficient viral translation.
Fertility intentions and child health in India: Women’s use of health services, breastfeeding, and official birth documentation following an unwanted birth

This study examines the relationship between women’s prospective fertility intentions and child health, measured via access to healthcare facilities for children and postpartum maternal behaviors that are indicative of future child health. We analyze two waves of nationally representative data (2005 and 2012) from the India Human Development Survey (IHDS). The analytic sample includes 3,442 non-pregnant, currently married women aged 18–40 in 2005 who participated in both rounds of the IHDS, and had at least one birth between 2005 and 2012. We investigate the influence of women’s prospective fertility intentions on access to benefits from the Integrated Child Development Services (ICDS), indicators of breastfeeding as recommended by the World Health Organization, and official documentation of births via birth certificates or registration. We find that 58 percent of births among women in the sample were labeled as unwanted. We use an adaptation of propensity score matching—the inverse-probability-weighted regression adjustment (IPWRA) estimator—and show that, after accounting for maternal and household characteristics that are known to be associated with maternal and child health, children who resulted from unwanted births were less likely to obtain any benefits or immunizations from the ICDS, to be breastfed within one hour of birth, and to have an official birth certificate. Results from this study have direct policy significance given the evidence that women’s fertility intentions can have negative implications for child health and wellbeing in the short and longer term.
Trajectory Optimization and Simulation of Aerospace Robotic Arm

Aerospace robotic arms have important applications in aerospace engineering (capture satellite, develop the technology of extra-vehicle activity (EVA), etc.) This paper first introduces the development and background of the Aerospace Robotic Arm. In later sections, a kinematics model of a Six-DOF manipulator is built based on DenavitHartenberg(D-H) method, then, the paper discusses an inverse kinematics solving method of the manipulator. At last, we show the simulation by integrating the use of SolidWorks, Matlab, and a number of their modules.