Miracle-dz/UniFAR-FTUs huggingface dataset:
Ternary Full Adder in CMOS-Memristor Technology

This paper presents a ternary full adder in CMOS-Memeristor technology. The design is based on unary operators and uses a ternary multiplexer to choose a particular unary operator. The paper proposes circuits for ternary unary operators such as cycle operator in CMOS-Memristor technology. The proposed designs are simulated in Cadence using CMOS UMC 130 nm and VTEAM model of memristor. The proposed ternary full adder saves 47 % of energy over a best existing design.
Design of Energy Efficient Hybrid Logic Full Adders

This paper is focused on the design and implementation of energy efficient hybrid logic full adders having low voltage and high performance using 90nm CMOS technology. XOR–XNOR circuits form the basic module in full adders and the performance of XOR-XNOR circuits has a large impact on the area, power and delay of the full adders Hence, new designs of XOR-XNOR circuits that consume less power and provide high speed with full swing outputs are proposed, designed and implemented in 90nm CMOS technology using Cadence tool. These proposed XOR/XNOR circuits along with sum and carry modules are used to design eight different energy efficient hybrid logic full adders. The full adders are also simulated using Cadence tool and their performance parameters are evaluated and compared.
Mapping The Potential Soil CH4 Diffusion Coefficient For Buenos Aires Province (Argentina)

Know potential CH4 uptake it is important to evaluate mitigations strategies of greenhouse gasses emissions in Argentina. One principal factor affecting CH4 uptake is CH4 soil diffusion coefficient (Ds) which depends strongly on bulk density and soil water content. So knowing potential Ds, the potential CH4 uptake can be indirectly estimated. Ds was estimated in Buenos Aires Province (Argentina) using three models that depend on the CH4 diffusion coefficient in air (corrected by temperature) and air-filled pore space. Temperature data from satellite (MODIS) and georeference soil parameters (WoSIS) were used to estimate Ds.Principal results showed that spatial variation of Ds is related principally to soil texture, bulk density and organic carbon, which regulates soil water content in the soil porosity. Temperature slightly affects spatial and temporal variation of Ds. Spatially, sectors of Buenos Aires Province with low and high potential Ds were detected, showing sectors with high and low potential CH4 uptake.
Correlative Probe and Electron Microscopy CPEM™ – The Novel Technology for 3D Material Surface Analysis

The direction of development in scientific instrumentation and analytical methods is the integration of various techniques into a compact apparatus. Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM) are well established and commonly used techniques for imaging the nanoworld. There are many applications of such devices especially in the field of material sciences, nanotechnology, semiconductors, and life sciences.
Forest resources of the Black Hills National Forest

conducted a inventory on the Hills National Forest using a nationally stan-dardized mapped-plot design (for see section was the inventory conducted? ” page This report presents the highlights of this 1999 periodic inventory using commonly requested variables and summaries. The data be summarized in other ways for different purposes (see further information” on the inside back The information presented in this is based on the IWFIA inventory Supplementary documentation and inventory terminology can be located in Additional data collected by the Black Hills National Forest and used separately or in combination with IWFIA data may produce varying re-sults. Changes since the inventory, such as the impact of more than 130,000 acres burned from large fires on the Forest (USDA 2002a), have not been incorporated into this report. Annual inventories will soon replace periodic inventories to help monitor these changes at shorter inter-vals. References to the “Black Hills” in this report pertain to National Forest System lands and not the general geo-graphic area.
Preventing Scan Attacks on Secure Circuits Through Scan Chain Encryption

Scan attacks exploit facilities offered by scan chains to retrieve embedded secret data, in particular, secret keys used by the device for data encryption/decryption in mission mode. This paper presents a scan attack countermeasure based on the encryption of the data written to or read from the scan chains. The secret-key management system already embedded in the device is used to provide appropriate keys for encryption of data flowing on the scan chains. The goal of the proposed solution is to counteract the scan-related security threats while preserving test and diagnosis efficiency provided by conventional design-for-testability techniques, as well as to allow debugging capabilities in mission mode. The proposed solution can deal with both stuck-at and transition-faults test schemes as well as single and multiple scan chain configurations using test data compression schemes. We will show that the proposed scheme provides expected test/diagnostic and debug facilities as classical scan design with marginal impacts on area, test time and design flows, while successfully preventing control and observation of data flowing in the scan chains by unauthorized users.
Early Detection of Invasive Exotic Trees Using UAV and Manned Aircraft Multispectral and LiDAR Data

Exotic conifers can provide significant ecosystem services, but in some environments, they have become invasive and threaten indigenous ecosystems. In New Zealand, this phenomenon is of considerable concern as the area occupied by invasive exotic trees is large and increasing rapidly. Remote sensing methods offer a potential means of identifying and monitoring land infested by these trees, enabling managers to efficiently allocate resources for their control. In this study, we sought to develop methods for remote detection of exotic invasive trees, namely Pinus sylvestris and P. ponderosa. Critically, the study aimed to detect these species prior to the onset of maturity and coning as this is important for preventing further spread. In the study environment in New Zealand’s South Island, these species reach maturity and begin bearing cones at a young age. As such, detection of these smaller individuals requires specialist methods and very high-resolution remote sensing data. We examined the efficacy of classifiers developed using two machine learning algorithms with multispectral and laser scanning data collected from two platforms—manned aircraft and unmanned aerial vehicles (UAV). The study focused on a localized conifer invasion originating from a multi-species pine shelter belt in a grassland environment. This environment provided a useful means of defining the detection thresholds of the methods and technologies employed. An extensive field dataset including over 17,000 trees (height range = 1 cm to 476 cm) was used as an independent validation dataset for the detection methods developed. We found that data from both platforms and using both logistic regression and random forests for classification provided highly accurate (kappa < 0.996 ) detection of invasive conifers. Our analysis showed that the data from both UAV and manned aircraft was useful for detecting trees down to 1 m in height and therefore shorter than 99.3% of the coning individuals in the study dataset. We also explored the relative contribution of both multispectral and airborne laser scanning (ALS) data in the detection of invasive trees through fitting classification models with different combinations of predictors and found that the most useful models included data from both sensors. However, the combination of ALS and multispectral data did not significantly improve classification accuracy. We believe that this was due to the simplistic vegetation and terrain structure in the study site that resulted in uncomplicated separability of invasive conifers from other vegetation. This study provides valuable new knowledge of the efficacy of detecting invasive conifers prior to the onset of coning using high-resolution data from UAV and manned aircraft. This will be an important tool in managing the spread of these important invasive plants.
Investigation of thermoelectric properties of 2D β-silicon monotelluride (site)

INVESTIGATION OF THERMOELECTRIC PROPERTIES OF 2D β-SILICON MONOTELLURIDE (SITE) Muhammad Hilal M.S. in Physics Advisor: Oğuz Gülseren September 2018 Thermoelectric properties of novel 2D silicon monotelluride (SiTe) are studied using first principles calculations. The plane wave method based on density functional theory as implemented in Vienna ab initio simulation package (VASP) is used to calculate the electronic structure. For the exchange correlation functionals, the generalized gradient approximation developed by Perdew-BurkeErnzerhof (PBE-GGA) is taken into account. The calculated band gap for β-SiTe is 1.83 eV which is in consistence with the previous theoretical data. The electronic and lattice transport properties are investigated using the Boltzmann transport equation. For the electronic transport properties, BoltzTraP code is used which relies on the Fourier interpolation of electronic band structure and thus requires a large k-sampling to optimize the interpolation and produce better results. The Seebeck coefficient obtained at room temperature is 290 μV/K and the figure of merit with κ` = 0 is 0.98. The density functional perturbation theory (DFPT) is used to calculate the 2 order harmonic and 3 order anharmonic force constants. The phonon dispersion and density of states are computed from the 2 order harmonic force constants using Phonopy code. The lattice thermal conductivity and other lattice dependent transport properties are calculated using both the harmonic and anharmonic force constants via ShengBTE program. The specific heat and lattice thermal conductivity at room temperature is 305.5 J/mol K and 1.35 × 10−3 W/m K, respectively. The figure of merit ZT for β-SiTe at room temperature using the κ` obtained from ShengBTE is 0.78 at 800k.
Use of Infrared Thermorgraphy in Animal Production

Infrared Thermography (TIV) is a non-invasive, safe technique that is capable of analysis and applicability in several areas. The objective of this study was to identify the importance of infrared thermography in production animals. In the study developed by Ferreira et al. (2011), TIV was used to evaluate the metabolic heat variations produced by chicks, the authors concluded that infrared thermography was able to efficiently detect the metabolic activity of juvenile birds. In goats, D’Alterio et al. (2011) evidenced unstable changes in the hull surface temperature flow, with the use of TIV. Graciano (2013) developed a study with pigs using the TIV and identified that the thermographic technique presents good efficiency for a pre-diagnosis of inflammatory changes and lesions, being able to be used as an aid, avoiding that reproducers are discarded. In view of the above, it is concluded that TIV presents applicability in different species of production animals, in addition, it is confirmed that TIV is relevant in the animal production area, because it functions as a body scanner, helping to show variations in the temperature of which may indicate metabolic changes or the onset of inflammatory processes.
Gamma irradiation response in photonic crystal and standard optical fiber Bragg grating sensors for radiation dosimetry

In this paper, we report the response of Cobalt-60 gamma irradiation on Photonic Crystal Fibre Bragg gratings (PCFFBGs) and standard commercial FBGs (STD-FBGs). Optical measurements were performed to determine the shift of the Bragg wavelength as a function of accumulated dose and relaxation time. To simulate real time conditions of a radiation dosimeter, the FBGs are examined through three consecutive radiation stages followed by very limited recovery times. We were able to obtain a Bragg wavelength shift with both sets of FBGs. The PCF-FBGs response included strong recovery after each irradiation compared to the STD-FBGs. This makes the PCF-FBGs strong candidates as optical fibre FBG sensors in the area of radiation dosimetry.
Computing with Memristor-based Nonlinear Oscillators

Among the recent disruptive technologies, volatile/nonvolatile memory-resistor (memristor) has attracted the researchers' attention as a fundamental computation element. It has been experimentally shown that memristive elements can emulate synaptic dynamics and are even capable of supporting spike timing dependent plasticity (STDP), an important adaptation rule for neuromorphic computing systems. The overall goal of this work is to provide an unconventional computing platform exploiting memristor-based nonlinear oscillators described by means of phase deviation equations. Experimental results show that the approach significantly outperforms conventional architectures used for pattern recognition tasks.
Assessing Genetic Algorithms for Placing Flow Processing-aware Control Applications

Future wireless access networks, such as 5G networks, demand very high traffic and a broad variety of network functions. While the former needs efficient management of the underlying backhaul network, the latter ensues a large amount of data processing. Finding good locations for data processing is a non-trivial task as data processing imposes many requirements on network resources but is crucial for network performance. In previous work, we have introduced the concept of control applications that perform both network control and data flow processing, tackling both aforementioned challenges simultaneously. To model this, we have formulated the Flow processingaware Control Application Placement Problem (FCAPP) and described first placement solution approaches. In this work, we assess whether Genetic Algorithms (GAs) are a viable approach for solving FCAPP.
Barrier Effect on MJO Propagation by the Maritime Continent in the MJO Task Force/GEWEX Atmospheric System Study Models

The simulated Madden–Julian oscillation (MJO) events in 27 general circulation models (GCMs) are identified using an MJO tracking method. The results suggest that the occurrence frequencies of simulated MJO events can represent a model’s ability to simulate several characteristics of the MJO to a certain extent during boreal winter, such as propagation range, strength, and termination longitude. All tracked MJO events are classified into those that propagate through the Maritime Continent (MC) (MJO-C) and those that do not (MJO-B), and the weakening and blocking effects on MJO propagation by the MC in GCMs were quantified. In general, if a GCM shows a stronger weakening effect on MJO strength over the MC, it tends to produce a stronger blocking effect on MJO propagation over the MC during boreal winter. The barrier effect of the MC on MJO propagation is exaggerated in most GCMs, while it can be underestimated in some GCMs, especially the coupled GCMs. Strong lower-tropospheric premoistening is identified ahead of the MJO convection center when it is over the central MC for MJO-C but not for MJO-B in most GCMs. Such strong premoistening is mainly attributed to the zonal gradient of lower-tropospheric easterly anomalies within the front Walker cell, which could be a precursor leading to the eastward propagation of MJO convection. In contrast to the observation, the role of the background sea surface temperature and land–sea precipitation contrast in the barrier effect on MJO propagation by the MC is not well captured by most GCMs.
Characterization of Deformation Twinning in Polycrystalline Cobalt: A Quantitative Analysis

Abstract Electron backscattering diffraction technique was used for a statistical analysis of twin formation in deformed polycrystalline cobalt. Deformation microstructure of samples plastically strained after a monotonous tensile test was studied by scanning and transmission electron microscopy. The analysis shows that the principal twin mode is the tension { 10 1 ¯ 2 } type. Multiple twin variants of this mode are present inside a grain. The higher occurrence corresponds to the variant with the misorientation of about 60° giving the best strain accommodation. It was found that besides grains favorably oriented, which are more prone to twin, there is also twinning in some grains not favorably oriented, which points out an influence of the local state of internal stress. Grain orientation has a more pronounced impact on twinning characteristics than the grain size. Favorably oriented grains exhibit a strong and positive correlation of the twin frequency, the twin area fraction, and the presence of multi-variant twins in a grain. On the other hand, large grains are more prone to twin, exhibit several twin variants but small twin area fraction.
INTEND AND FUNCTIONING OF FIR FILTER NETWORK FOR RECONFIGURABLE FUNCTIONS

Transpose-form finite impulse response (FIR) structures are inherently pipelined and support multiple constant multiplication (MCM) ends up in the vital saving of computation. However, the transpose form configuration doesn't directly support the blocking process in contrast to the direct-form configuration. we've got derived a general multiplier based architecture for the projected transpose-form block filter for reconfigurable applications. A low-complexity style victimization MCM theme is additionally conferred for the block implementation of fastened FIR filters. ASIC synthesis result shows that the projected structure for block-size four and filter-length sixty-four involve forty-second less area-delay product (ADP) ADP and four-hundredth fewer EPS than the most effective obtainable FIR structure projected for reconfigurable applications. For an equivalent filter length and therefore the same block size, the projected structure involves thirteen less ADP and 12.8% fewer EPS than that of the prevailing direct-from block FIR structure. Supported these findings, we tend to gift a theme for the choice of direct-form and transpose-form configuration based on the filter lengths and block-length for getting area delay and energy economical block FIR structures.
Algorithm for detection the QRS complexes based on support vector machine

The efficiency of computer ECG analysis depends on the accurate detection of QRS-complexes. This paper presents an algorithm for QRS complex detection based of support vector machine (SVM). The proposed algorithm is evaluated on annotated standard databases such as MIT-BIH Arrhythmia database. The QRS detector obtained a sensitivity Se = 98.32% and specificity Sp = 95.46% for MIT-BIH Arrhythmia database. This algorithm can be used as the basis for the software to diagnose electrical activity of the heart.
Finishing performance of die-sinking EDM with ultrasonic vibration and powder addition through pulse train studies

Abstract Die-sinking electrical discharge machining (EDM) is widely used in die and mold-making industry. Finish EDM conditions are often selected to produce good quality surfaces. Attempts to enhance the finishing capabilities using ultrasonic vibration and powder-added dielectric medium have been reported in the literature. However, the changes in the gap phenomena with ultrasonic assistance and powder addition have not been analyzed. In this article, finish EDM of hardened D3 steel has been carried out based on full factorial design of experiment with three levels of setting voltage, setting current and pulse on time. The performance of ultrasonic assisted and graphite powder-added EDM are evaluated by analyzing the voltage and current pulse trains in finishing operation for the first time. Based on two new parameters, namely energy expended over a second (E) and ratio of energy due to sparks in relation to total discharge energy (PF), the results are discussed and also compared with those obtained with conventional EDM for selected conditions. Even though E of 102.9 J (PF = 0.862) with ultrasonic vibration is higher than E of 43.0 J (PF = 1.0) with powder mix, the molten metal is removed effectively from the gap by ultrasonic vibration which results in a relatively better surface. The micrographs of cross-section and surface of the workpieces obtained using optical and scanning electron microscopes, respectively, also reveal their relative performance.
Machine Learning based Drowsiness Detection in Classrooms

The Major objective of this proposed work is to detect the mood swings of face and drowsiness especially in schools and graduate levels. This work is supported by the machine learning and various studies on existing methods of drowsiness detection suggested the impact of artificial intelligence in identifying the face mood swings. Thisproposed system follows the machine learning models and it shows a better performance. The system has been implemented in classrooms. The base of thispaperwork involves OpenCV library of python which acts as a great tool for image processing, computer vision, and object tracking. The Haar cascade algorithm is used for face detection which recognizes faces of students in real-time video and follows the stages of Haar transformations. The Haar cascade uses the eyeball movement as a parameter is distinguish the various mood swings of the students. The main intention of thisproposed system is to reduce the drowsiness level among the students in classroom environment by providing alert feedback at centralised manner. The proposed model has 85.3% and 95.3% accuracies for detecting the mood swings and eye recognition. The models are developed and tested on SVM, NN, KNN and RF where the NN has the maximum accuracy of 84% and this work shows the overall improvement of 15% in all the primary aspects.
Analyzing data from experimental studies: A latent variable structural equation modeling approach.

This article illustrates the use of structural equation modeling (SEM) procedures with latent variables to analyze data from experimental studies. These procedures allow the researcher to remove the biasing effects of random and correlated measurement error on the outcomes of the experiment and to examine processes that may account for changes in the outcome variables that are observed. Analyses of data from a Project Family study, an experimental intervention project with rural families that strives to improve parenting skills, are presented to illustrate the use of these modeling procedures. Issues that arise in applying SEM procedures, such as sample size and distributional characteristics of the measures, are discussed.
Marbling Grading Framework Applied on Meat Boutique Environment

Bovine meat commercialization has an important role in the general food market scenario. The beef quality evaluation is realized through many ways, being one of the parameters the intramuscular fat amount (marbling). This evaluation is often made by a visual approach, so the process is subjective and susceptible to some errors sources. The use of Computer Vision techniques results in an automatized, non-subjective, fast and accurate method for evaluation. This paper presents the modeling and development of a Computer Vision System for Marbling evaluation, applied on a meat Boutique, localized in Londrina - PR. The proposed System uses a Computer Vision approach to control the features of the marbling analysis tool, aiming to satisfy sanitary requirements for non-contamination of the analyzed samples. Besides that, multiples samples on the scene are supported by our application. The proposed Computer Vision System has proved to be suitable for implantation in a production environment, like a meat Boutique.