Miracle-dz/UniFAR-FTUs huggingface dataset:
Relay Deployment and Network Optimization for NOMA-Enabled Double-Layer Airborne Access Vehicular Ad Hoc Networks

In this paper, we design a nonorthogonal multiple access (NOMA)-enabled double-layer airborne access vehicular ad hoc networks (VANETs) architecture with a tethered high-altitude platform (HAP), multiple miniaturized unmanned aerial vehicles (UAVs) and vehicles, based on which the relay deployment and network optimization problems are investigated. Specifically, based on our designed architecture, we first propose a UAV relay deployment scheme by using the particle swarm optimization algorithm to maximize network coverage ratio. Then, to guarantee the performance of network edge vehicles, we introduce the NOMA technique into the double-layer airborne access VANETs. Moreover, the network optimization problem is formulated as a joint UAV height optimization, channel allocation, and security assurance problem, such that the total achievable data rate is maximized. Challenged by the coupled relationship between the optimization variables, we decouple the optimization problem as two subproblems and devise an efficient iterative algorithm to optimally allocate according to the golden section method and the matching theory. Finally, simulation results demonstrate that the proposed NOMA-enabled double-layer airborne access VANETs architecture can achieve significant performance superiority in terms of the total achievable data rate.
Diagnosis of Hordeum vulgare Genomic Profile: Review

This review represent plants genetic diversity (PDG) generally in crop plant and especially in Barley (Hordeum vulgare), can be studied (PDG) and stored as a (PGR) plant genetic resources as gene bank , DNA library for saved genetic material at long time and crops improvement can be utilized in breeding programs strategies in future. In this study observed the significance of plant genetic diversity (PGD) and (PGR) especially on agriculturally important crops , analysis of plant genomic using molecular markers. Barley is a well important studies crops using as a model for study genetic plant, cultivated barley Hordeum vulgare easily hybridization by genetic fingerprinting with wiled barley Hordeum spontaneum. The molecular markers showed their relation with locus of geographic factors and imposed stresses. Here, discussed barley genomic through relationship between genotype and phenotype traits using molecular markers useful for genetic physiological maps construction.
Development of carbonated sweet orange RTS beverage

Attempts were made in the present investigation in order to develop a carbonated ready to serve (RTS) beverage from sweet orange juice. The matured and freshly harvested fruits of Cv. Nucellar were washed and peeled manually. The juice was extracted by using screw type juice press followed by filtration. The beverage was prepared by adjusting the juice level (10, 15, 20%) with sugar syrup (60° Brix TSS and 0.5% acidity) and then carbonated at 80 and 100 psi pressure respectively. The resultant RTS beverage was then analyzed for various physico-chemical and sensorial quality characteristics. The study revealed that the RTS beverage prepared by using the 20% sweet orange juice along with 0.3% acidity, 11.7° Brix TSS and carbonated at 100 psi pressure was found significantly superior with respect to various quality characteristics over other combinations.
A coherent multichannel demonstrator

The paper describes an advanced coherent multichannel (CMC) communications demonstrator that has been designed by the RACE 1010 consortium. This fully engineered demonstrator examines the application of CMC techniques to broadband signal distribution (e.g. television and high-definition television) in the local loop. Ten 140 Mbit/s digitised video signals are transmitted on ten optical carriers 10 GHz apart. Up to 1000 receiver terminals can be served from a single central transmitter assembly. The paper explores the system operation, system specifications, and subsystem results that have been achieved.
Formant Tracking Using Quasi-Closed Phase Forward-Backward Linear Prediction Analysis and Deep Neural Networks

Formant tracking is investigated in this study by using trackers based on dynamic programming (DP) and deep neural nets (DNNs). Using the DP approach, six formant estimation methods were first compared. The six methods include linear prediction (LP) algorithms, weighted LP algorithms and the recently developed quasi-closed phase forward-backward (QCP-FB) method. QCP-FB gave the best performance in the comparison. Therefore, a novel formant tracking approach, which combines benefits of deep learning and signal processing based on QCP-FB, was proposed. In this approach, the formants predicted by a DNN-based tracker from a speech frame are refined using the peaks of the all-pole spectrum computed by QCP-FB from the same frame. Results show that the proposed DNN-based tracker performed better both in detection rate and estimation error for the lowest three formants compared to reference formant trackers. Compared to the popular Wavesurfer, for example, the proposed tracker gave a reduction of 29%, 48%, and 35% in the estimation error for the lowest three formants, respectively.
Health literacy and associated factors among undergraduates: A university-based cross-sectional study in Nepal

Health literacy is one of the most critical aspects of health promotion. Limited health literacy is also accounted for adverse health outcomes and a huge financial burden on society. However, a gap exists in the level of health literacy, especially among undergraduates. This study aimed to assess the levels of health literacy and its socio-demographic determinants among undergraduate students of Tribhuvan University, Nepal. A web-based cross-sectional survey was conducted among 469 undergraduate students from five institutes of Tribhuvan University, Nepal. The 16-item short version of the European Health Literacy Survey Questionnaire (HLS-EU-Q16) was used to measure students’ health literacy levels. Associated factors were examined using Chi-square tests followed by multivariate logistic regression analyses at the level of significance of 0.05. Nearly 61% of students were found to have limited health literacy (24.5% had “inadequate” and 36.3% had “problematic” health literacy). Female students (aOR = 1.6, 95% CI: 1.1–2.5), students from non-health related majors (aOR = 1.9, 95% CI: 1.2–3.0), students with unsatisfactory health status (aOR = 2.8, 95% CI: 1.7–4.5), students with poor financial status (aOR = 2.9, 95% CI: 1.2–6.8) and students with low self-esteem (aOR = 2.5, 95% CI: 1.5–4.1) were significantly more likely to have limited health literacy. The majority of the undergraduates were found to have limited health literacy. Gender, sector of study, self-rated health status, self-rated financial status, and self-esteem were significantly associated with limited health literacy. This study indicates university students should not be assumed to be health-literate and interventions to improve students’ health literacy especially for those whose majors are not health-related should be implemented. Further studies using a longer version of the health literacy survey questionnaire and qualitative methods to explore more on determinants of health literacy are recommended.
Autonomous Vehicle Evaluation: A Comprehensive Survey on Modeling and Simulation Approaches

In recent years, autonomous vehicles (AVs), which observe the driving environment and lead a few or all of the driving duties, have garnered tremendous success. The field of AVs has been developing rapidly and has found many applications. As a safety requirement by policymakers, these vehicles must be evaluated before their deployment. The evaluation process for AVs is challenging because crashes are rare events, and AVs can escape passing predefined test scenarios. Therefore, capturing crashes and creating real test scenarios should be considered in order to have an evaluation approach that represents the real-world scenarios. One evaluation approach is based on the naturalistic field operational test (N-FOT), in which prototype AVs are driven by volunteers or test engineers on the roads. Unfortunately, this approach is time-consuming and costly because one needs to drive thousands of miles to experience a police-reported collision and nearly millions of miles for a fatal crash. Another approach is the Accelerated Evaluation method. The core idea of the Accelerated Evaluation approach is to modify the statistics of naturalistic driving so that safety-critical events are emphasized. This paper presents a brief survey of the advances that have occurred in the area of the evaluation of partly or fully AVs, starting with naturalistic field operational tests (N-FOTs). The review goes on to cover test matrix evaluation, worst-case scenario evaluation (WCSE), Monte Carlo simulations, and accelerated evaluation (AE). We also present all the simulation-based and agent-based modeling approaches that do not follow any evaluation protocol listed above. This study provides a scientific analysis of each of the evaluation techniques, focusing on their advantages/disadvantages, inherent restrictions, practicability, and optimality. The results reveal that the accelerated evaluation approach outperforms naturalistic field operational tests (N-FOTs), test matrix evaluation, worst-case scenario evaluation (WCSE), Monte Carlo simulations methods in some of the car-following, and lane-change studies when using specific models. Moreover, the agent-based model and augmented and virtual reality approaches show promising results in AVs evaluation. Furthermore, integrating machine and deep learning into the available AV evaluation methods can improve its performance and generate encouraging outcomes.
TARe: Task-Adaptive in-situ ReRAM Computing for Graph Learning

ReRAM-based Computing-in-Memory (CiM) architecture has been considered an ideal solution to neural networks, by conducting in-situ matrix multiplications without moving the neural parameters from memory cells. However, we found that keeping the parameters static in ReRAM cells, i.e. weight-static processing, is not the sole choice to implement emerging graph neural networks (GNNs) that operate on the input of ultra large graphs. Therefore, we propose TARe, a Task-Adaptive CiM architecture that supports multiple different in-situ computing modes for Graph Learning. With the proposed novel hybrid in-situ computing architecture, TARe achieves 451.98× speedup on average over the baseline in SOTA GNN workloads.
A Review on Freshness of the Fish by Different Methods

: The healthcare system is the one which develops and delivers clinical and integrated software solutions for healthcare facilities which are specialized under pharmacy radiology etc. and are those which reduces cost and errors and thereby improving patient health and the access to information. Fish is an incredible sustenance to expend for us. It is sound tasty however it has an exceptionally restricted time span of usability. After that restricted time consuming the fish can harm individual’s wellbeing. From that point, angle begins including in security viewpoints for example being free from unsafe microscopic organism’s parasites or chemicals. There are few hints to choose whether a fish is new or not like checking its eyes, smell or gills. All these methods require in-depth subject knowledge experience about the fish and it also gives results which change from person to person. There are four highlights used to decide fish freshness, three of which are connected with shape and the other is identified with the shading. Ninety percent of the test fish have been correctly recognized by using the shape features. Colour features helped in successfully classifying the test fishes. The above result proves that the technique which is proposed can successfully be used to detect the freshness of the fish. Here we are going to discuss all the different methods and find out the optimal method in determination of freshness of the fish. fish freshness including tangible assessment, microbial review, synthetic estimations of dampness content, unpredictable mixes, protein changes, lipid oxidation, and adenosine triphosphate (ATP) disintegration (K esteem), physical estimations, and remote material pollution location.
Comparison between theoretical and measured microstrip gap parameters involving anisotropic substrates

In this paper, experimental results are presented for microstrip symmetrical-gap discontinuities. The experimental technique is based on the measurement of the resonant frequencies of several gap-coupled rectangular microstrip resonators. In particular, gap discontinuities on anisotropic dielectric and two-layer composite substrates have been investigated. Reasonably good agreement has been found in most cases between theoretical data [obtained by means of the excess charge technique in the spectral domain (EC-SDA)] and experimental data, even though the theoretical results have been obtained by using a quasi-static approach.
An Effective Simulation Methodology of Quantum Nanostructures based on Model Order Reduction

A quantum simulation methodology developed previously based on model order reduction is applied to a 2D nanostructure. The approach is derived from proper orthogonal decomposition that projects the nanostructure from its physical domain onto a function space represented by a finite set of POD modes. Numerical solution data of the wave function are collected from the Schrödinger equation to adapt the variation of the energy band induced by electric fields. The POD modes generated from the data are thus able to account for the variation of electric field. Two different models based on different training methods are explored. Their efficacy and accuracy are investigated.
Description of an entirely reconfigurable architecture dedicated to the current vector control of a set of AC machines

Complex industrial applications use several AC machines. It is a necessity to centralize the control of all the machines in order to reduce the cost and to optimize the reliability and the efficiency of the control system. In this paper, the authors present an original architecture dedicated to the current vector control of a set of AC machines. It is exclusively based on FPGAs (field programmable gate arrays), and is, for this reason, fully reconfigurable. The whole algorithm is distributed in several dedicated elementary processors. Each one of them is implemented in an FPGA component. Thanks to pipelined operations, a very short global computing time has been obtained. With the actual system, the current components in a rotating frame of up to four AC machines can be controlled at a sampling rate of 20 kHz. Experimental results are also presented to validate the study.
Design, development and characterization of an integrated multispectral polarimetric sensor system

In this thesis, a new type of integrated imaging sensor is introduced to detect multispectral and polarimetric signatures in an infrared scene. The sensor is a stack consisting of an infrared detector array, and an array of multispectral and polarimetric filters. In this first phase of the research, a single-pixel sensor was built. Multispectral filters were initially fabricated for the 3-5 micron waveband on sapphire substrates and polarimetric filters on silicon substrates. These were characterized separately and in mechanical contact as a single unit. The transmission characteristics of both filters show excellent agreement with the theoretical results. When the filters are integrated into an imaging sensor, such a sensor is anticipated to improve image contrast with sensor-fusion post processing. In addition, it will offer portability and robustness because of its integrated nature. Thesis Supervisor: Cardinal Warde Title: Professor, Department of Electrical Engineering and Computer Science
RDOF: Deployment Optimization for Function as a Service

Function as a service (FaaS) simplifies the runtime resource management of cloud applications and enables fine-grained scaling and billing at the function level, thus becoming the most widespread serverless paradigm today. Cost-effective use of FaaS entails appropriately deploying individual functions. We propose in this paper RDOF1, a model-driven approach to deployment optimization for FaaS. RDOF predicts the performance of a FaaS-based application by instantiating a layered queueing network and finds the optimal configuration of each function such that the total operating cost is minimized under the specified performance requirements. We have validated RDOF on Amazon Web Services (AWS) and implemented it in an online tool that operates on TOSCA metamodels.
Modeling traffic flow emissions

The main topic of this thesis is the development of light-duty vehicle dynamic emission models and their integration with dynamic traffic models. Combined, these models constitute fundamental components to support the development and assessment of traffic management policies, and the optimization of their parameters, to alleviate the negative impacts of road traffic. We develop and implement a dynamic model of emissions ( 2 CO , CO , HC , and x NO ) and fuel consumption for light-duty vehicles. The model is derived from regression-based and load-based emissions modeling approaches, and effectively combines their respective advantages. The model is calibrated for two vehicle categories using FTP as well MEC01 driving cycles data. The US06 driving cycle is used to validate the estimation capabilities of the proposed model. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well to results obtained with CMEM, a well-known load-based dynamic emission model. Furthermore, the results indicate that the model runs fast, and is relatively simple to calibrate. We propose a framework for the integration of dynamic emission models with nonmicroscopic dynamic traffic models, that do not estimate vehicle acceleration. A probabilistic model of acceleration is designed and implemented to link the traffic and the emission models. The model provides an experimental distribution of the accelerations for any given speed and road type. The framework is applied to integrate the dynamic emission model developed in this thesis with a mesoscopic dynamic traffic flow model. Using a hypothetical case study, we illustrate the potential of the combined models to estimate the effects of route guidance strategies, which are one of numerous examples of dynamic traffic management strategies, on traffic travel times and traffic emissions. In presence of incidents, it is shown that route guidance can reduce total travel times as well as total emissions. Thesis Supervisor: Ismail Chabini Title: Associate Professor, Civil and Environmental Engineering
Effect of positive pulse charge waveforms on the energy efficiency of lead-acid traction cells

The effects of four different charge methods on the energy conversion efficiency of 300 ampere-hour lead-acid traction cells were investigated. Three of the methods were positive pulse charge waveforms; the fourth, a con~ stant current method, was used as a baseline of comparison. The positive 0\ 0\ pulse charge waveforms were; 120 Hz full wave rectified sinusoidal (FWSR), 120 I ~ Hz silicon controlled rectified (SCR); and 1 kHz square wave (SW). The constant current charger was set at the time average pulse current of each pulse wave form, which was 150 amperes. The energy efficiency does not include charger losses. The lead-acid traction cells were charged to 70% of rated ampere-hour capacity in each case. The results of charging the cells using the three different pulse charge waveforms indicate there was no significant difference in energy conversion efficiency when compared to constant current charging at the time average pulse current value.
Agregação de pontos de vista de stakeholders utilizando o Value-Focused Thinking associado à mapeamento cognitivo

Abstract This study proposes a new approach for aggregating the opinions of different stakeholders based on value-focused thinking combined with cognitive mapping. This approach was applied to determine selling prices, focusing on the particular case of a compounding pharmacy in southern Brazil. This method provides a better understanding of the problem with respect to the members involved. This paper also identifies the implications of working with individual stakeholders, generating different models and combining the viewpoints to obtain a unique result in the process of product pricing. Keywords Establishment of sales price. Decision making. Value-focused thinking. Cognitive map. of Operational Research, v. 92, n.3, p. 537-549,1996. http://dx.doi. org/10.1016/0377-2217(96)00004-5KIRKWOOD, C. W. Strategic Decision Making: Multi Objective Decision Analysis with Spreadsheets. Belmont: Wadsworth Publishing Company,Methods in Group Decision Making: Past Applications 1997.MORAIS, D. C. ; ALMEIDA, A. T. Water network rehabilitation: A group decision-making approach. Water SA, v. 36, n. 4, p. 487-493, 2010. http://dx.doi. org/10.4314/wsa.v36i4. 58425MORAIS, D. C. ; ALMEIDA, A. T. Group decision making on water resources based on analysis of individual rankings. OMEGA- The International Journal of Management Science, vol. 40, p. 42-52, 2012.SANTOS, J. J. Fundamentos de Custos para a Formacao do Preco e do Lucro. 5. ed. Sao Paulo: Atlas, 2005.SARTORI, E. Gestao de precos. Sao Paulo: Atlas, 2004.WARFIELD, J. N. A science of Generic Design: Managing complexity through systems design. 2nd ed. Iowa State University Press, 1994.WINTER, M. Problem structuring in Project management: an application of soft systems methodology (SSM). Journal of the Operational Research Society, v. 57, p. 802-812,http://dx.doi. org/10.1057/palgrave.2006. jors.26020505
Trust-Region Method with Deep Reinforcement Learning in Analog Design Space Exploration

This paper introduces new perspectives on analog design space search. To minimize the time-to-market, this endeavor better cast as constraint satisfaction problem than global optimization defined in prior arts. We incorporate model based agents, contrasted with model-free learning, to implement a trust-region strategy. As such, simple feed-forward networks can be trained with supervised learning, where the convergence is relatively trivial. Experiment results demonstrate orders of magnitude improvement on search iterations. Additionally, the unprecedented consideration of PVT conditions are accommodated. On circuits with TSMC 5/6nm process, our method achieve performance surpassing human designers. Furthermore, this framework is in production in industrial settings.
Evaluation and collaboration in creating online audio descriptions of visual art

AccesArte is an accessibility project that is part of the internship programme at Kaleidoscope, a non-profit organization founded by the authors to apply audio description (AD) research to developing accessibility programmes. The project consists of ADs of a thematic selection of visual artworks, and the development of eclectic and experience-oriented AD types. It uses online, open access videos and performs a formative and summative evaluation of the resources, with the latter being online, open and ongoing. The goal of this article is to offer a detailed description and critical analysis of the project, with an emphasis on the formative evaluation process. In this regard, the formative evaluation has allowed us to include blind and partially sighted (BPS) consultants in the process, improve resource quality, and enrich the interns’ learning experience.