Miracle-dz/UniFAR-FTUs huggingface dataset:
High-strength concrete columns: a design guide

Synopsis The use of high-strength concrete (HSC) has increased significantly in recent years due to its improved performance characteristics when compared with normal-strength concrete (NSC). Current design codes, however, are predominantly based on data derived from tests on NSC. Furthermore, the extrapolation of NSC design rules to HSC is not always conservative and can lead to unsafe designs. Extensions to the NSC provisions of current codes to encompass HSC have been published, but their advice is often ignored by engineers, because either their recommendations are not mandatory, or the codes do not give clear direction on their limitations. This paper compares the behaviour of HSC with NSC and highlights the brittle nature of HSC under axial loading. Specific design and detailing requirements for achieving adequate ductility in HSC columns are reviewed and discussed. The paper describes how sufficient ductility can be achieved by using an appropriate confining pressure provided by the column links. A typical design example and RC details are included to illustrate how an appropriate level of ductility can be achieved. Nomenclature Ac net cross-sectional area of concrete in a column Acc area of concrete core in a column bounded by the centreline of the outermost links Ae effective area of concrete core Ag gross area of column cross section Asc area of vertical reinforcement Ash cross-sectional area of a single of a link in a column bc centre to centre width of outermost links in rectangular column C confinement parameter dc centre to centre depth of outermost links in rectangular column
ON-LSTM : An Empirical Analysis

In this project we attempt to apply a novel approach to a well known problems in natural language processing, namely langua modelling and text classification. The paper on Ordered Neurons takes a different approach in this domain with the underly hypothesis being that natural language is hierarchically structured: smaller units (e.g. noun phrases) are nested within larger un (e.g. clauses). While the different units of an LSTM can learn to track information at different time scales, the standard architect does not impose this sort of strict hierarchy. In particular, we aim to evaluate a novel RNN framework proposed recently in IC 2019, 'ON-LSTM (https://arxiv.org/pdf/1810.09536.pdf)' which explicitly integrates the latent tree structure into RNN and focuses modeling the hierarchy of constituents. The paper claims that it outperforms state-of-the-art LSTM based language model like AW LSTM (https://arxiv.org/pdf/1708.02182.pdf) which we intend to verify by evaluating on Toxic Comment Classificat (https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data) dataset hosted on Kaggle.
Design and Structural Analysis of the Solid-State Recorder for Missile Flying Parameters Recording

While the flying test of the missile, many kinds of parameters need to be recorded and the recording instruments are working in harsh environment. For this particular application a Solid-state recorder had been designed for obtaining and recording flying parameters of the missile, including data acquisition module, power management module, the central control module, a data storage module, the reading interface module, etc. Meanwhile, analyzed structures of the Solid-state recorder and completed thermal analysis and impact stress analysis of the structure using finite element analysis software ANSYS. The results had shown that the recorder can survive well in the flying test of the missile and the recorder had been applied to the actual trial and got accurate and reliable data.
Exponential Time Differencing-Padé Finite Element Method for Nonlinear Convection-Diffusion-Reaction Equations with Time Constant Delay

In this paper, ETD3-Padé and ETD4-Padé Galerkin finite element methods are proposed and analyzed for nonlinear delayed convection-diffusion-reaction equations with Dirichlet boundary conditions. An ETD-based RK is used for time integration of the corresponding equation. To overcome a well-known difficulty of numerical instability associated with the computation of the exponential operator, the Padé approach is used for such an exponential operator approximation, which in turn leads to the corresponding ETD-Padé schemes. An unconditional L numerical stability is proved for the proposed numerical schemes, under a global Lipshitz continuity assumption. In addition, optimal rate error estimates are provided, which gives the convergence order of O(k + h) (ETD3-Padé) or O(k + h) (ETD4-Padé) in the L norm, respectively. Numerical experiments are presented to demonstrate the robustness of the proposed numerical schemes.
Asynchronous Demodulation Method for Four SSB arranged on Frequency Axis in Mobile Radio Path using Hilbert Transform

— In this paper, an asynchronous demodulation method for a four-single sideband (SSB) signal arranged on the frequency axis is developed to support burst mode transmission in a mobile radio path and to achieve greater data throughputs. When a reduced pilot carrier is placed at the center of the 4-SSB signal, it is guarded by lower and upper sidebands, that is, this scheme is classified into a tone-in-band (TIB) system. Digital signal processing (DSP) processors are useful for implementing a Hilbert transform. However, we have for a long time neglected introducing it into the demodulation process of SSB signals.
LED Display Image Correction Based on Computer Simulation

For the purposes of correcting the LED display image, a method based on computer simulation is proposed. First, the development of the LED display panel is introduced. Second, analyze the causes of the problem which image in LED display panel has serious high non-uniformity, and introduce the existed correction techniques which are used to reduce the non-uniformity of LED display image. Simultaneously, point out the ground for shortcomings of these techniques. Third, describe the principle of correction method based on computer simulation detail from two steps, which are the luminous collection and luminous copulation. Forth, describe the realization steps of this method in accordance with the third step. Finally, this method is supplied in a LED display panel, whose resolution is 640×480. Experimental results show that this method is able to reduce the non-uniformity of images from 11.06% to 0.98%.
A 900-MHz CMOS low-phase-noise voltage-controlled ring oscillator

A 900-MHz two-stage CMOS voltage-controlled ring oscillator (VCO) with good phase-noise performance is presented. Implemented in a 0.5-/spl mu/m CMOS technology and at 2.5-V supply voltage, the VCO has a wide operating frequency range from 661.5 MHz to 1.27 GHz with a peak VCO gain (K/sub VCO/) of -630 MHz/V. At 900 MHz, the phase noise of the VCO is -105.5 dBc/Hz at 600-kHz frequency offset with low power consumption of 15.4 mW. The gain and phase mismatches are less than 0.25 dB and 0.5/spl deg/, respectively, which corresponds to an image rejection of better than 31 dB. The chip area is only 125/spl times/102 /spl mu/m/sup 2/.
A new test structure for extracting extrinsic parameters in double-polysilicon bipolar transistors

A new test structure for parameter extraction is presented and implemented in a double-polysilicon bipolar junction transistor (BJT) process. The test structure is basically a real BJT, but without the intrinsic base. The test structure allows extraction of the base, collector and emitter impedances, and the extrinsic base-collector capacitance.
RevEAL: Single-Trace Side-Channel Leakage of the SEAL Homomorphic Encryption Library

This paper demonstrates the first side-channel attack on homomorphic encryption (HE), which allows computing on encrypted data. We reveal a power-based side-channel leakage of Microsoft SEAL prior to v3.6 that implements the Brakerski/Fan-Vercauteren (BFV) protocol. Our proposed attack targets the Gaussian sampling in the SEAL's encryption phase and can extract the entire message with a single power measurement. Our attack works by (1) identifying each coefficient index being sampled, (2) extracting the sign value of the coefficients from control-flow variations, (3) recovering the coefficients with a high probability from data-flow variations, and (4) using a Blockwise Korkine-Zolotarev (BKZ) algorithm to efficiently explore and estimate the remaining search space. Using real power measurements, the results on a RISC-V FPGA implementation of the SEAL (v3.2) show that the proposed attack can reduce the plaintext encryption security level from 2128 to 24.4. Therefore, as HE gears toward real-world applications, such attacks and related defenses should be considered.
Classification of Arabic News Texts with Fasttext Method

: Access to information is getting easier day by day because of the entering our lives of the computer and especially the internet. As the internet access becomes easier and the internet users increase, the amount of data is growing every second. However, in order to access correct information, data must be classified. Classification is the process of separating data according to a certain semantic category. Dividing digital documents into semantic categories significantly affects the availability of the text. In this study, a text classification study was carried out on a data set obtained from different Arabic news sources. Firstly, the news texts were pre-processed and trunked. Pretreated texts were classified by K-Neighbors Classifier, Gaussian Naive Bayes, Multinomial Naive Bayes, Logistic Regression, Random Forest Classifier, Support Vector Classifier and Decision Tree Classifier methods after the FastText method was vectorized. According to the results of the study, the highest success rate was obtained by classification of the text obtained with the FastText vector model with approximately 90.36% with Logistic Regression.
Estimation of Traffic Volume on Rural Local Roads

Traffic volumes on local roads have not received much attention from highway planners and researchers, although local roads constitute the majority of road mileage in a state. In recent years the need for reliable estimates of vehicle-miles of travel on local roads has been recognized for the analysis of air quality and highway safety issues. To provide a better understanding of traffic volumes on local roads and to explore alternative methods for estimation, data from Georgia were analyzed by using different statistical procedures. The findings of this analysis are presented, along with the results of an attempt to develop a mathematical model for estimation of local road traffic volumes.
Electrical antenna volume for a scale of downsizing

The author considers the electrical antenna volume for the scale of downsizing for the measured data of a disk loaded monopole antenna and the analysis of the square patch antenna. The antenna downsizing is obtained by reducing the bandwidth and by accepting poor efficiency, which is easily introduced in the normalized electrical volume. The difference in near field for antennas of different unloaded Q is studied. <<ETX>>
THEORETICAL AND APPLIED BASIS FOR CREATION OF SPATIALLY- DIFFERENTIATED SYSTEMS OF SOIL QUALITY MANAGEMENT BASED ON SPACE SCANNING DATA

Global trends in agricultural production and environmental management require the mandatory use of geoinformation technologies and Earth remote sensing data as a basis for informational support for effective management of land and soil resources. Therefore, it is important to develop a methodology for using space scanning data to create spatiallydifferentiated soil quality management systems, which take into account the quantitative estimates of spatial soil variation and the results of pedotransfer modeling to evaluate soil quality and create optimal agrotechnologies. Experimental studies in different regions of Ukraine showed the effectiveness of the developed technology for soil decoding by multispectral space data with high spatial resolution to determine soils, which are different in complex assessment of soil physical quality for the diagnosis of especially valuable, optimal and modal parameters of soils, their degraded and underproductive kinds. Coherent analysis of the results of space image classification and geostatistical processing of soil field surveys is effective for a reasonable extrapolation of evaluation results at large territories and the development of agrotechnologies, which provide optimal conditions for development of agricultural plants and increase their
Toward Net-Zero Base Stations with Integrated and Flexible Power Supply in Future Networks

The energy consumption and carbon emissions of base stations (BSs) raise significant concerns about future network deployment. Renewable energy is thus adopted and supplied to enable the net-zero (or zero-carbon) BS. However, due to severe inconsistency between renewable energy generation and power demand, the conventional one-to-one power supply architecture could cause large waste and low utilization of renewable energy. In this article, we design a many-to-many power supply architecture for BSs to maximize the utilization of renewable energy. More specifically, we strategically group multiple renewable energy generators into virtual cells to serve multiple BSs in an integrated way, thus minimizing the inconsistency between the renewable energy generation and power demand. To finetune the power mismatch between power supply and demand in each virtual cell, we propose software-defined techniques to flexibly control the discharging/charging of a battery energy storage system. Illustrative results from a case study demonstrate that high renewable energy utilization can be achieved with the proposed architecture and mechanisms.
Plant root PET: visualization of photosynthate translocation to roots in rice plant

Roots are essential to plants for uptake of water and nutrients. For the improvement of crop production, it is necessary to understand the elucidation of the root development and its function under the ground. Especially, photosynthate translocation from plant leaves to roots is an important physiological function that affects the root elongation, adaptation to the soil environment and nutrients uptake. To evaluate the translocation dynamics to roots, positron emission tomography (PET) and 11C tracer have been used. However, the spatial resolution is degraded at roots that develop around the peripheral area of field of view (FOV) due to parallax errors. In this study, to overcome this problem, we developed a small OpenPET prototype applying four-layer depth-of-interaction detectors. We demonstrated the imaging capability of 11C-photosynthate translocation to rice roots that develop throughout the entire PET field. We also tried to obtain structural information of roots by high-throughput X-ray computerized tomography (CT) system using the same test plant. As a result, we succeeded in visualizing the root structure that developed around the peripheral region of FOV and imaging the accumulation of 11C-photosynthate to the roots in those areas without degrading the spatial resolution. From obtained images, we also succeeded in evaluating the translocation dynamics varied by roots. The combined use of the high-throughput CT system and the OpenPET prototype was demonstrated to be appropriate for structural and functional analysis of roots.
InaCORS-BIG Service For Practice Survey

Badan Informasi Geospasial (BIG) is a government agency engaged in the field of Geospatial Information (IG). BIG provides several services that can be accessed by the general public and related to IG. One of the services provided by BIG is the Indonesia Continuously Operating Reference System (InaCORS). InaCORS is divided into various services, as Rinex data services, Online Post-Processing, RTK NTrip, and Mobile InaCORS. This study aims to determine the effectiveness and accuracy of InaCORS services for GNSS surveys using the Rapid Static method and Network RTK. The rapid static survey data is processed using online post-processing services and Network RTK (iMax, Max, and Nearest) will use InaCORS points as a base reference. This study also uses the results of the Total Station tool as comparison data. The results showed that the average value of the difference between the rapid static coordinates and the TS observations was dN = 0.353 m dE = 0.180 m and dZ = 0.233 m, while the Network RTK and TS coordinates were dN = 0.408 m dE = 0.184 m and dZ = 0.176 m.
Artificial neural network for solving multi-parameter optimization problems

An artificial neural network (ANN) is a mathematical or computational model that simulates the structure and function of biological neural networks used to evaluate or approximate functions at given points. After developing the training algorithm, the resulting model will be used to solve image recognition problems, control problems, optimization, etc. In the process of ANN training, the algorithm of backpropagation is used in the case of convex optimization functions. The article is analyzed test functions for experiments and also study the effect of the number of ANN layers on the quality of approximation in cases one-, two- and three-dimensional. The backpropagation method is improved during the experiments with the help of adaptive gradient, as a result of which more accurate approximations of the functions are obtained. This article also presents the numerical results of test functions.
Appendices A Negative Sampling

We train CoPER by minimizing the binary cross-entropy between for predicted distribution over answer entities. However, one challenge is that the training data only contains triples of the form (es, r, et) and there is no clear way to obtain negative samples of the form “this entity is not a correct answer to this question. ” A common approach to address this challenge is to consider all answers that appear in the training set as correct answers and all other entities in the KG as wrong answers. However, this approach exhibits two issues. First, it can become very expensive for large KGs as all the entities are involved in the computation of the loss function for each training example. In addition to that, it is not necessarily correct because some of the entities treated as incorrect answers during training are the very answers we are asked to infer at test time. To alleviate these two issues, we use an alternative approach based on that of Bordes et al. (2013) and Yang et al. (2015). Instead of considering all possible alternative answers as wrong, we uniformly sample a fixed number of alternative entities, for each positive triple, and use them as negative training examples. Our experiments show that this helps boost performance and also significantly improve efficiency.
PARALLEL ALGORITHMS FOR LOW-RANK APPROXIMATIONS OF MATRICES AND TENSORS BY LAWTON MANNING

v Chapter
Numerical method for solving the piecewise constant source inverse problem of an elliptic equation from a partial boundary observation data

We present results of numerical investigation of the source term recovery in a boundary value problem for an elliptic equation. An additional information about the solution is considered as its normal derivative taken on a part of the boundary. Such source inverse problem is related with inverse gravimetry problem of determining an inhomogeneity from gravitational potential anomalies on the Earth’s surface. We propose an iterative method for numerical recovery of the source term on the base of minimization of the observation residual by a gradient type method. The numerical implementation is based on finite element approximation using the FEniCS scientific computing platform and the dolfin-adjoint package. The capabilities of the developed computational algorithm are illustrated by results of numerical solutions of two dimensional test problems.
Hardware Phase Shift Hybrid Precoding Designs For Multi-User Massive MIMO Systems

Hybrid precoding is a challenging design for massive MIMO systems that involves a combination of analog and digital processing, aiming to maximize the spectral efficiency (SE). Most works on hybrid precoding focus on the single phase shifter (SPS) implementation to adapt the phase from RF chains to antennas. In this paper we propose to develop the double phase shifter (DPS) and the fixed phase shifter (FPS) in both single-path and multi-path configuration. Simulation results certify a significant improvement for both proposed implementations with high hardware efficiency (HE) and high spectral efficiency especially in multi-path environment.
Data-Driven Approaches to User Interface Design: A Case Study

The most common reason for software product failure is misunderstanding user needs. Analysing and validating user needs before developing a product can allow to prevent such failures. This paper investigates several data-driven techniques for user research and product design through prototyping, customer validation, and usability testing. The authors implemented a case study software product using the proposed techniques, and analyses how the application of UX/UI research techniques affected the development process. The case study results indicate that preliminary UX/UI research before the development reduces the cost of product changes. Moreover, the paper proposes a set of metrics for testing the effectiveness of UX/UI design.
SENTIMENT ANALYSIS: AN APPROACH BASED ON TEXTUAL DATA AND PRODUCTS REVIEWS

Sentiment analysis is one of the most important approaches used to analyze the data and identify sentiment expressed by the customers on the text. Opinion mining is also the name given for sentiment analysis. In the Internet large amount of text data is getting generated either in the form of suggestion, feedbacks, tweets or comments. The Amazon web services are generating lots of text data through customer reviews. Analyzing this data will help the online retailers to understand customer expectation and also provide shopping experience that can increase the sale. The Sentiment Analysis helps to identify the positive, negative and neutral information from the customer reviews. Most of the researchers have developed a technique for the sentiment analysis. Machine learning algorithms are used for analyzing text data. This work concentrates on the Amazon customer reviews on electronics devices such as kindle, fire TV stick, computer etc which includes basics product information like rating, reviews, etc. Using Machine Learning Algorithm based on text reviews the algorithm can predict positive or negative response given by the customers.