Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and Synthesis of a New Class of Low Side Lobe Planar Arrays

Numerical techniques for designing planar arrays with low side lobe level often require memory intensive optimization algorithms and also initialization in the form of some known values of radiation pattern parameters beforehand information that may not be available when designing arrays. A few analytical methods exist in the literature that can be used to design rectangular lattices of isotropic elements for desired half-power beamwidth and side lobe level, but the number of elements of the array often should be known before the design process. Some array designs based on analytical techniques may suffer from severe performance limitations, an example is the uniformly excited array which cannot produce side lobe levels below ̶ 13.3 dB. The goal of this study is to present an analytical technique for synthesis of planar arrays that, for specified radiation pattern requirements, not only provides quick solutions for the required number of elements and its distribution along the length and width of the array rectangular lattice, but also produces low side lobes without any limitation. A new class of non-uniformly excited equally spaced planar arrays is introduced and investigated in this study. The new array uses the patterns of uniformly excited linear arrays as its building blocks and has a separable element current distribution, hence making it mathematically convenient to analyze its radiation properties in terms of those of its constituent linear arrays. The proposed planar array does not suffer from the side lobe level limitation of uniformly excited planar arrays, and its synthesis, due to the analytical nature of description of its radiation properties, does not require iterative procedures that are inherent to numerical techniques. Radiation characteristics of the proposed planar array, including directivity, side lobe level, half-power beamwidths, far-field three dimensional radiation patterns, and element excitation currents, are examined and simulation results for several example cases are presented. The analysis culminates with successfully mapping a continuous radiation pattern to discrete element currents in a rectangular lattice geometry. The synthesis procedure is validated by successfully designing various planar arrays with desired requirements in terms of side lobe level and half-power beamwidths in the principal planes. Several design examples are presented. Radiation characteristics of the synthesized arrays are compared with the desired design requirements which were used as input information in the synthesis process. For the cases studied, the achieved performance characteristics are close to the desired ones. Analysis and Synthesis of a New Class of Low Side Lobe Planar Arrays
Bonus-Malus premiums under the dependent frequency-severity modeling

ABSTRACT A Bonus-Malus System (BMS) in insurance is a premium adjustment mechanism widely used in a posteriori ratemaking process to set the premium for the next contract period based on a policyholder's claim history. The current practice in BMS implementation relies on the assumption of independence between claim frequency and severity, despite the fact that a series of recent studies report evidence of a significant frequency-severity relationship, particularly in automobile insurance. To address this discrepancy, we propose a copula-based correlated random effects model to accommodate the dependence between claim frequency and severity, and further illustrate how to incorporate such dependence into the current BMS. We derive analytical solutions to the optimal relativities under the proposed framework and provide numerical experiments based on real data analysis to assess the effect of frequency-severity dependence in BMS ratemaking.
Resonant-Tunnelling Diodes as PUF Building Blocks

Resonant-Tunnelling Diodes (RTDs) have been proposed as building blocks for Physical Unclonable Functions (PUFs). In this paper we show how the unique RTD current-voltage (I-V) spectrum can be translated into a robust digital representation. We analyse 130 devices and show that RTDs are a viable PUF building block.
Standards-Based Grading: an Examination of Assessment Options

Methods of assessing and measuring student learning have long been examined for their effectiveness in providing valid and reliable reports. While letter grades have historically been the traditional system of grading and the common choice of educators and parents, the growing importance of standards-based instruction has created a need to rethink options. There are challenges to all options of assessment however, evaluating student growth through the use of a standards-based grading system is reported to provide more clarity and value to the process of assessment.
Improving the Lifetime of Non-Volatile Cache by Write Restriction

The attractive features such as low static power and high density exhibited by the Non-Volatile Memory (NVM) technologies makes them a promising candidate in the memory hierarchy, including caches. However, the limited write endurance with the write variations governed by the access patterns and the applied replacement policies reduce the chance of NVMs as a successor of SRAM. These write variations are of concern as they not only breakdown the NVM cells but also reduce the effective lifetime. This paper proposes efficient techniques to mitigate the intra-set write variation to improve the lifetime of the NVM cache. Our first two techniques partition the cache into windows of equal size and distribute the writes uniformly across the cache set by employing the window as write-restricted or read-only. The selection of the window in these techniques is by rotation or with the help of counters. In our third technique, different cache ways are employed as a write-restricted over the period of execution to distribute the writes uniformly. Experimental results using full system simulation show the significant reduction in intra-set write variation along with improvement in the cache lifetime.
Third-order Optical Nonlinearities for Integrated Microwave Photonics Applications

The field of integrated photonics aims at compressing large and environmentally-sensitive optical systems to micron-sized circuits that can be mass-produced through existing semiconductor fabrication facilities. The integration of optical components on single chips is pivotal to the realization of miniature systems with high degree of complexity. Such novel photonic chips find abundant applications in optical communication, spectroscopy and signal processing. This work concentrates on harnessing nonlinear phenomena to this avail. The first part of this dissertation discusses, both from component and system level, the development of a frequency comb source with a semiconductor mode-locked laser at its heart. New nonlinear devices for supercontinuum and second-harmonic generations are developed and their performance is assessed inside the system. Theoretical analysis of a hybrid approach with synchronously-pumped Kerr cavity is also provided. The second part of the dissertation investigates stimulated Brillouin scattering (SBS) in integrated photonics. A fully-tensorial open-source numerical tool is developed to study SBS in optical waveguides composed of crystalline materials, particularly silicon. SBS is demonstrated in an all-silicon optical platform.
Provocateurs and triggers: Induction of antigen -specific responses to the colonic resident microbiota and susceptibility to colitis

Inflammatory bowel disease is a chronic inflammation of the gastrointestinal tract (GI) that develops in part as a result of an aberrant immune response to enteric bacteria in the GI tract. Prior studies indicate that Helicobacter bilis colonization of immune competent, defined-flora (DF) mice induced antigen-specific responses to their resident flora, in the absence of colitis. We hypothesize that H. bilis colonization of DF mice perturbs mucosal homeostasis and, thus, alters tolerance to the commensal flora and increases the host’s sensitivity to an inflammatory insult. Defined flora mice were colonized with Helicobacter bilis for up to 20 weeks prior to treatment with low-dose (1.5%) dextran sulfate sodium (DSS). Mice were evaluated for gross and histological lesions as well as cellular and humoral responses in comparison to controls. In comparison to DSS treated or H. bilis colonization alone, mice dually treated with H. bilis and DSS developed significantly (p < .05) increased gross and histopathological lesions including cecal atrophy, decreased colon length, and histological inflammation. Serum IgG2a responses to antigens derived from the enteric flora were increased compared to controls. Evaluation of the proximal colon indicated an increase in mucosal IL-17, IFN-γ, and TNF-α after colonization and/or DSS treatment. The magnitude of antigen-specific T cell proliferation increased with time, as Foxp3 expression declined; however, lesions did not increase in severity. Susceptibility to DSS-induced colitis was associated with increased antigen-specific reactivity to the enteric flora and mucosal expression of inflammatory cytokines. In conclusion, these studies demonstrate that perturbation of the microbial ecology following colonization with a mildly pathogenic bacteria, such as H. bilis, may induce antigen-specific Th1 and Th17 immune responses, thus, predisposing the host to colitis following exposure to an otherwise innocuous inflammatory insult.
A Unified Clock and Switched-Capacitor-Based Power Delivery Architecture for Variation Tolerance in Low-Voltage SoC Domains

Correctly operating digital SoC domains at their target frequencies require the addition of supply voltage (<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula>) guardbands to account for supply droop events and temperature variation. These guardbands degrade processor energy efficiency, especially in low-voltage sensor and IoT applications due to increased delay sensitivity to temperature and <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> variation. In this paper, we present an all-digital unified clock and power (UniCaP-SC) architecture that combines switched-capacitor (SC)-based voltage control and clock frequency regulation into a single loop to significantly reduce required <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> guardbands. A UniCaP-SC test chip consisting of a near-threshold voltage (NTV) ARM Cortex-M0 processor was fabricated in 65-nm CMOS. The fully integrated system enables all-digital construction, aggressive <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> margin reduction, and continuous <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> scalability using SC-based voltage converters while no additional decoupling capacitance (decap). Test-chip measurements demonstrate a 16% <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> reduction corresponding to a 94% <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> margin recovery or an equivalent <inline-formula> <tex-math notation="LaTeX">$3.2\times $ </tex-math></inline-formula> increase in the operating clock frequency (<inline-formula> <tex-math notation="LaTeX">$f_{\mathrm{ clk}}$ </tex-math></inline-formula>).
Ethics and Research With Children: A Case-Based Approach

After years of debate and controversy, fundamental questions about the morality of pediatric research persist: Is it ever permissible to use a child as a means to an end? How much authority should parents have over decisions about research that involves young children? What should be the role of the older child in decisions about research participation? How do the dynamics of hope and desperation influence decisions about research involving dying children? Should children or their parents be paid for participation in research? What about economic incentives for doctors, researchers and the pharmaceutical industry? Most importantly, how can the twin goals of access to the benefits of clinical research and protection from research risk be reconciled?
POS TAGGING BAHASA INDONESIA DENGAN MAXIMUM ENTROPY MENGGUNAKAN STANFORD POSTAGGER

Pada saat ini pemrosesan bahasa alami menggunakan bahasa Indonesia sulit dikembangkan. Hal tersebut dikarenakan kurangnya library yang menunjang dalam memroses bahasa alami dalam bahasa Indonesia. Stanford postagger menyediakan library dalam POS (Part of Speech) Tagging, akan tetapi tidak meliputi bahasa Indonesia. Dalam hal ini, penulis menyediakan library dengan cara membuat data latih, kemudian melatihnya menggunakan kelas maximum entropy pada Stanford postagger. Hasil data latih dicobakan dengan kalimat-kalimat dan dokumen-dokumen. Hasil dari sistem dibandingkan dengan ahli yang memberikan hasil cohens kapa sebesar . Kata Kunci: pemrosesan bahasa alami, POS tagging, Stanford posstagger
Achieving real-time video summarization on commodity hardware

Achieving Real-Time Video Summarization on Comodity Hardware Wesley Taylor Master’s Thesis Faculty of Science (Computer Science) University of Ontario Institute of Technology 2018 We present a system for automatic video summarization which is able to operate in real-time on commodity hardware. This is achieved by performing segmentation to divide a video into a series of small video clips, which are further reduced or eliminated with the assistance of highly efficient low-level features. A numerical score is then assigned to each segment by our model trained using a set of highperformance hand-crafted features. Finally, segments are selected based on their score to generate a final video summary. On our benchmark dataset, we achieve results competitive to other methods. In cases where our accuracy is lower than competitive methods, we achieve significantly higher performance. We additionally present methods for generating additional summaries almost instantly, and for learning user preferences over time—two processes which are often overlooked in work on video summarization, but essential for real-world use.
Leaf shape simulation of castor bean and its application in nondestructive leaf area estimation

The leaf shape and leaf area measurement are crucial in plant growth modeling. The castor bean leaf is large, palm-shaped with multiple clefts. The leaf shape simulation and leaf area estimation were less studied. The circular model and nonrectangular hyperbolic model were developed to describe the standard leaf shape of castor bean in this study, providing a model for simulating the leaf shape and a nondestructive way for estimating the leaf area respectively. In addition, a formula was established to estimate the leaf area by the parameter of the standard leaf shape of castor bean. Based on validation results, the circular model fits the landmarks and nonrectangular hyperbolic model fits the lobe margins very well. The leaf area was accurately estimated by using the established formula. This study could provide a theoretical reference for leaf visualization, a nondestructive and easy way to estimate the leaf area for other complex leaves with multiple lobes. Keywords: leaf shape, leaf area, geometrical characteristics, mathematical model, image processing, plant growth modeling DOI: 10.25165/j.ijabe. 20191204.4040 Citation: Wei H L, Li X M, Li M, Huang H. Leaf shape simulation of castor bean and its application in nondestructive leaf area estimation. Int J Agric & Biol Eng, 2019; 12(4): 135–140.
The semi‐analytical method for time‐dependent wave problems with uncertainties

This paper provides a constructive procedure for the computation of approximate solutions of random time‐dependent hyperbolic mean square partial differential problems. Based on the theoretical representation of the solution as an infinite random improper integral, obtained via the random Fourier transform method, a double approximation process is implemented. Firstly, a random Gauss‐Hermite quadrature is applied, and then, the evaluations at the nodes of the integrand are approximated by using a random Störmer numerical method. Numerical results are illustrated with examples.
Artificial Intelligence in Automated Sorting in Trash Recycling

A computer vision approach to classify garbage into recycling categories could be an efficient way to process waste. This project aims to take garbage waste images and classify them into four classes: glass, paper, metal and, plastic. We use a garbage image database that contains around 400 images for each class. The models used in the experiments are Pre-trained VGG-16 (VGG16), AlexNet, Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and, Random Forest (RF). Experiments showed that our models reached accuracy around 93%.
Introduction, analysis and asymptotic behavior of a multi-level manpower planning model in a continuous time setting under potential department contraction

Abstract A mathematical model in a multi-level manpower planning setting is developed and analyzed incorporating the divisions of an organization’s personnel into several homogeneous groups. The proposed framework builds upon recent research to develop, via the continuous time scale, a departmental model encompassing employees flows within departments (intra-departmental transitions), as well as transfers among departments (inter-departmental transitions). Management-wise, this is a common practice under certain conditions as in restructuring and rightsizing ventures both in private industries and in the public sector. After establishing the baseline differential equations of the system, an investigation follows regarding the system’s limiting behavior integrating the concept of department contraction which can be seen as an indirect and mild control that can be exercised on the manpower system. It is proved that under a set of conditions, the system’s limiting structure exists and is specified. The aforementioned asymptotic analysis can be utilized to predict, in the long run, future stock structures of departments and thus, in the case where these structures diverge from the desired ones, identify departments that could be considered as candidates for probable rightsizing or mergers. The paper concludes with a numerical illustration and some concluding remarks.
The Impact of Initial Condition and Warm Conveyor Belt Forecast Uncertainty on Variability in the Downstream Waveguide in an ECWMF Case Study

Perturbations to the potential vorticity (PV) waveguide, which can result from latent heat release within the warm conveyor belt (WCB) of midlatitude cyclones, can lead to the downstream radiation of Rossby waves, and in turn high-impact weather events. Previous studies have hypothesized that forecast uncertainty associated with diabatic heating in WCBs can result in large downstream forecast variability; however, these studies have not established a direct connection between the two. This study evaluates the potential impact of latent heating variability in the WCB on subsequent downstream forecasts by applying the ensemble-based sensitivity method to European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasts of a cyclogenesis event over the North Atlantic. For this case, ensemble members with a more amplified ridge are associated with greater negative PV advection by the irrotational wind, which is associated with stronger lower-tropospheric southerly moisture transport east of the upstream cyclone in the WCB. This transport is sensitive to the pressure trough to the south of the cyclone along the cold front, which in turn is modulated by earlier differences in the motion of the air masses on either side of the front. The position of the cold air behind the front is modulated by upstream tropopause-based PV anomalies, such that a deeper pressure trough is associated with a more progressive flow pattern, originating from Rossby wave breaking over the North Pacific. Overall, these results suggest that more accurate forecasts of upstream PV anomalies and WCBs may reduce forecast uncertainty in the downstream waveguide.
Veech groups and extended origamis

In this paper, we deal with flat surfaces of finite analytic type with two distinct Jenkins-Strebel directions. We show that such a flat surface is characterized by decomposition into parallelograms which consists of informations of angles, moduli, and neighboring structure similar to origami. The structure similar to origami plays a role of an invariant under affine deformations and we can characterize the Veech group of flat surface of this kind combinatorially.
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks

To backpropagate the gradients through stochastic binary layers, we propose the augment-REINFORCE-merge (ARM) estimator that is unbiased, exhibits low variance, and has low computational complexity. Exploiting variable augmentation, REINFORCE, and reparameterization, the ARM estimator achieves adaptive variance reduction for Monte Carlo integration by merging two expectations via common random numbers. The variance-reduction mechanism of the ARM estimator can also be attributed to either antithetic sampling in an augmented space, or the use of an optimal anti-symmetric "self-control" baseline function together with the REINFORCE estimator in that augmented space. Experimental results show the ARM estimator provides state-of-the-art performance in auto-encoding variational inference and maximum likelihood estimation, for discrete latent variable models with one or multiple stochastic binary layers. Python code for reproducible research is publicly available.
Optimal control governed by stochastic elliptic equations with regular states

This study deals with an optimal control problem subject to a stochastic elliptic equation with Dirichlet boundary condition and in which the state process is regular on a stochastic Hilbert space. We prove the existence and uniqueness of the optimal control and provide furthermore necessary and sufficient optimality conditions. The optimal solution is obtained in the case where there is no constraint. Our method is based on variational theory of elliptic boundary problems in Hilbert spaces.
Chained Predictions of Flight Delay Using Machine Learning

Flight delay creates major problems in the current aviation system. Methods are needed to analyze the manner how delay propagates in the airport networks. Traditional methods are inadequate to the task. This paper presented a new machine learning based air trafﬁc delay prediction model that combined multi-label random forest classiﬁcation and approximated delay propagation model. To improve the prediction performance, an optimal feature selection process is introduced and demonstrated to have better performance than directly using all the features of available datasets. Departure delay and late arriving aircraft delay are shown to be the most important features for delay prediction. To utilize these two features, a delay propagation model is proposed as a link to connect them to build a chained delay prediction model. Given the initial departure delay, the chained model is demonstrated to have the ability to predict the ﬂight delay along the same aircraft’s itinerary. By up-dating the actual departure delay with the iteration number along the itinerary, the model’s accuracy can be further improved. Our application results clearly demonstrate the value of machine learning and delay propagation for analyzing and predicting the air trafﬁc delay in daily operation.