Miracle-dz/UniFAR-FTUs huggingface dataset:
TROPHY: Efficient Greedy Transmission of Data Packet using Trophy (TAD-hoc) Protocol along with Greedy algorithm in VANET

A vehicular ad-hoc network is a subcategory of MANET. All the mobile nodes, are endowed in VANET for real-time application for communicating, and transmitting a message under the vehicle-to-vehicle communication. This VANET technology improves the road safety to reduce traffic congestion issues under a transportation system. In this paper, we have to propose a protocol called Trophy (TAD-Hoc) protocol along with greed behavior routing algorithm to improve the overall performance and efficiency of packet transmission under effective utilization with the desired authentication. This trust worthy authentication in VANET generates a Routing authentication key (TROPHY) to give an overall security under a network with improved performance under various parameters such as end-to-end delay, transmission range, and power consumption. Whenever the packet is transmitted over a network by using a trophy, along with a greedy behavior routing algorithm, it sends a packet in a trusty manner and gives efficient performance under security because of the authentication key. When compared to DSR, AODV this TAD-Hoc protocol which gives an efficient performance under network. The packet will be discarded if it duplicates.
Block Error Detection Driven Nonlinearity Compensation for Optical Fiber Communications

The perturbation-based nonlinearity compensation (NLC) method is considered in conjunction with a forward error correction (FEC) code that is capable of detecting block errors. The FEC decoding is performed prior to the NLC, and NLC is then performed only for blocks, that could not be decoded correctly. The total NLC complexity is thus dramatically reduced to down to 1% in some cases w.r. t. the standard, hard decision-directed NLC performed prior to the FEC decoding. Negligible FEC decoding complexity increase is required for the subsequent decoding of the nonlinearity-compensated blocks. The proposed method achieves and sometimes outperforms the standard perturbation based NLC at a fraction of the overall complexity. Polar codes are used to exemplify the method.
Path Loss and Delay Spread Characterization in a 26 GHz mmWave Channel Using the Ray Tracing Method

The application of millimeter wave band is a promising technique to achieve the high rates requirements in the Fifth Generation (5G) of wireless communications. In Brazil, the frequency spectrum regulatory agency must use the 26 GHz band to mmWave applications in 5G. This paper presents results of a 26 GHz micro-cellular urban channel obtained from a 3D ray tracing simulation. The applied ray tracing simulation is based on the Shooting-and-Bouncing Rays (SBR) method, which considers reflected and diffracted rays. The considered scenario of simulation is based on the mapping of Manaíra and Jardim Oceania neighborhoods, seafront of João Pessoa city, Brazil. As results, are presented the characterization of the path loss exponent, shadow fading standard deviation and RMS delay spread statistics.
Input-to-State Stability and Stabilization of Sampled-Data Systems Under Aperiodic Sampling and Random Sampling

In this article, input-to-state stability (ISS) and stabilization are examined for sampled-data systems under deterministic aperiodic sampling and random sampling, respectively. Using the direct design method, the sampled-data systems are transformed into switched systems with switched time-varying delays. First, the ISS definition and criterion appropriate for these systems are provided. Based on this, the ISS criterion on sampled-data systems under deterministic aperiodic sampling is given. Second, after the stochastic ISS (SISS) definition and criterion are provided for switched nonlinear systems with randomly switching delays, the SISS criterion for the sampled-data systems under random sampling is provided. All of the ISS and SISS definitions are given in the form of $\mathcal {KL}$ function that is quite elegant and easy to work with. Then, sufficient conditions for input-to-state stabilization are obtained for sampled-data linear systems under deterministic aperiodic sampling and random sampling, respectively, via the Lyapunov-Krasovskii method. Finally, based on the criteria, a piecewise controller is designed by the matrix inequality approach for a sampled-data linear time invariant system, and simulation results are provided to illustrate our design method. The main conclusion of this article is that sampling intervals will affect the controller design of the systems, and the ISS properties are maintained using a piecewise controller.
Power Delivery Networks for Embedded Mobile SoCs: Architectural Advancements and Design Challenges

Conventional power delivery networks (PDNs) and power management techniques using off-chip power converters with bulky passive components cannot meet the ever-evolving power delivery requirements of high-performance modern system-on-chips (SoCs). In SoCs, heterogeneous components, including multi-core processors and mixed-signals peripheral circuits, require state-of-the-art PDNs to provide high-quality power-on-demand with minimum latency, simultaneously achieving the small-factor, high conversion efficiency, and minimum current consumption. To satisfy these power delivery requirements, various PDNs have been developed over the past decades, such as the conventional architectures using off-chip power converters, architectures using in-package power converters and fully-integrated power converters, and heterogeneous architectures (off-chip power converters and on-chip regulators). This paper reviews these architectural advancements of the PDNs and their advantages and limitations, which leads us to discuss a heterogeneous PDN structure consisting of a highly efficient off-chip switching-mode power converter and multiple highly precise small linear regulators integrated on chip at point-of-load locations. The heterogeneous PDN has been proved one of the most suitable architectures to achieve high-quality fine-grained on-chip power delivery and management in SoCs. This paper also discusses unified voltage and frequency regulators (UVFRs), which support dynamic-variation-aware dynamic voltage and frequency scaling (DVFS) for fine-grained power management in multi-core processors. Based on the UVFR, we propose a modified heterogeneous PDN using frequency-referenced digital low-dropout regulators (FR-DLDOs) for more efficient DVFS, eliminating the need for band-gap circuits to provide reference voltages. As an exemplary implementation of FR-DLDO for this PDN, we present an FR-DLDO with a transient-boost control, which accelerates the transient response. The transient-boost control is activated dynamically only when an abrupt change happens out of the steady state. The implemented FR-DLDO fabricated in a 40-nm CMOS process outperforms other FR-DLDOs in the figure-of-merit and peak power efficiency while driving 40 mA of load current.
Simulation Applications in Humanitarian Logistics: A Systematic Literature Review

Humanitarian logistics involve planning, acting and controlling situations in which vulnerable people are involved. Simulation techniques can successfully represent the dynamics of disasters, characterized by situations of complexity and uncertainties. This work aims to review papers that apply simulation techniques to solve problems that arise in disaster situations. To accomplish this, we analysed 33 papers published from 2010 to 2019, indexed in Scopus or Web of Science databases, that used simulation techniques to solve humanitarian problems. The descriptive analysis conducted found out that there is a small but increasing number of papers over time. Discrete events simulation and system dynamics are the most used techniques. From the content analysis we find that most research focuses on short term decisions and solving problems related to post-disaster response in unforeseen events. However, topics such as evacuation and transportation of victims are still unexplored.
A Review on Deep Learning in Minimally Invasive Surgery

In the last five years, deep learning has attracted great interest in computer-assisted systems for Minimally Invasive Surgery. The straightforward accessibility to images in surgical interventions makes deep neural networks enormously powerful for solving classification problems in complex surgical scenarios. The objective of this work is to provide readers a survey on deep learning models applied to minimally invasive surgery, identifying the different architectures used depending on the application, the results achieved until now, and the publicly available surgical datasets that can be used for validating new studies. A total of 85 publications have been extracted from manual research from four databases (IEEE Xplorer, Springer Link, Science Direct, and ACM Digital Library). After analyzing all these studies, they have been classified into four applications: surgical image analysis, surgical task analysis, surgical skill assessment, and automation of surgical tasks. This work provides a technical description of these works and a comparison among them. Finally, promising research directions to advance in this field are identified.
A Novel Modified Lightning Attachment Procedure Optimization Technique for Optimal Allocation of the FACTS Devices in Power Systems

The Flexible AC Transmission Systems (FACTS) are the static power electronic devices that are installed and used in AC transmission networks to enhance the capability of transferring the power for providing the controllability and stability. However, the optimization of site and size of these devices is a crucial task due to their high capital cost and practical capabilities. In this paper, the optimal reactive power dispatch (ORPD) embedded with two effective controllers including the Static VAR Compensator (SVC) and Thyristor Control Series Capacitor (TCSC) is solved using a Modified Lightning Attachment Procedure Optimizer (MLAPO). The searching capability of basic LAPO is enhanced and the stagnation of basic LAPO is avoided by application of levy flight distribution and spiral orientation motion. The optimization for these devices is for reducing the power losses, voltage deviations, and the operating cost. MLAPO is examined and tested on modified IEEE30 and IEEE57 bus-standards considering SVC and TCSC. The effectiveness of MLAPO is further analyzed and compared with the outcomes of the well-known optimization techniques namely LAPO, PSO, ALO, EO, MPA, WOA and SCA with and without FACTS devices.
A Model-Order Reduction Approach for Electromagnetic Problems With Nonaffine Frequency Dependence

The aim of this paper is to present a novel model-order reduction (MOR) technique for the efficient frequency-domain finite-element method (FEM) simulation of microwave components. It is based on the standard reduced-basis method, but the subsequent expansion frequency points are selected following the so-called sparsified greedy strategy. This feature makes it especially useful to perform a fast-frequency sweep of problems that lead to systems of equations exhibiting a nonaffine frequency dependence. This property appears, for example, when the excitation of the problem is characterized by a frequency-dependent waveguide mode pattern, or when the computational domain includes materials with frequency-dependent permittivity or permeability tensors. Moreover, the new MOR scheme can be also used to accelerate the frequency sweep of problems with many excitations, for which the standard reduction algorithms tend to be time-consuming. Its effectiveness and accuracy is verified through analysis of three microwave structures: planar microstrip branch-line coupler, three-port waveguide junction with ferrite post, and an eighth-order dual-mode waveguide filter.
Graphene oxide filled optical fiber micro-cavity based temperature sensor

This work describes an optical fiber temperature sensor based on a micro-cavity filled with graphene oxide (GO). The cavity was produced from the recycling of an optical fiber destroyed by the catastrophic fuse effect. The optical reflection spectrum of the GO filled cavity shifts towards higher wavelengths as the temperature increases. This change is up to 26.1 nm in the temperature range from 10 to $50^{\circ}\mathrm{C}$. Compared with other fiber based devices, the proposed sensor has greater sensitivity with the advantages of being a cost-effective solution for the temperature monitoring.
Comparison of Cortical and Cutaneous Vascular Hemodynamic Changes in Hypoxia by Using in Vivo Skull and Skin Optical Clearing Techniques

Hypoxia occurs in various pathophysiological conditions. Especially, brain can be seriously affected by the oxygen deficiency. However, challenges exist in optically monitoring cerebral hemodynamics with high resolution. As an easily-detected vessel bed, peripheral skin is a potential target for predicting cerebrovascular hemodynamic changes. However, the similarities and differences between cerebral and cutaneous hemodynamics during hypoxia are still unclear. One of the main reasons is that optical imaging techniques are fundamentally depth/resolution-limited due to high scattering properties of turbid tissue. Fortunately, in vivo tissue optical clearing techniques can efficiently overcome these problems, and avoid the side-effects of surgical windows. In this work, we simultaneously monitor the changes in cortical and cutaneous microvascular blood oxygen and blood flow under the assistance of in vivo skull and skin optical clearing techniques, and quantitatively compared the differences between cerebral and cutaneous arteriovenous functional responses to the hypoxic stimulus. The results indicated that the variation tendency of blood oxygen response might be more similar, and cutaneous vascular blood oxygen response has the potential to serve as an accessible indicator for revealing cerebrovascular dysfunction. Moreover, it provides a feasible approach to realize visualization of in vivo monitoring cerebral and cutaneous microvascular reactivity with minimal invasiveness.
An Application of Kubernetes Cluster Federation in Fog Computing

This demonstration aims at showcasing an application of a cluster federation to increase the elasticity and resilience of a Fog Computing system. Federation is performed by means of the Kubernetes Cluster Federation (KubeFed), a framework we augmented with a two-phase workload placement mechanism that smartly distributes applications’ microservices among the federated infrastructure. Despite KubeFed has been generally used in a multi-cloud environment for workloads split on different cloud providers avoiding the lock-in, in this demonstration we show that it can also be used for implementing a decentralized control plane in a highly distributed architecture where networking issues should be taken into account.
STFT Based on Bandwidth-Scaled Microwave Photonics

Short-time Fourier transform (STFT) is a fundamental concept that enables the observation of dynamic spectral evolution for non-stationary signals. Broadband STFT based on digital signal processing (DSP) usually has limited acquisition frame rate, which is inherently constrained by the performance limitations of present DSP engine. The further extended acquisition frame rate can be achieved by all-optical spectrum analysis approaches, while the frequency resolution is usually worse than 1 GHz. In this article, STFT based on bandwidth-scaled microwave photonics is proposed, where the requirement for dispersion is relaxed and the attendant transmission delay in dispersive media is greatly reduced. Moreover, the frequency resolution towards MHz level could be expected in the proposed STFT. We prove that “bandwidth scaling” combined with periodic wavelength-to-time mapping (WTM) mathematically agrees with the definition of STFT. The method of customizing system parameters according to the requirements of ultrafast spectrum measurement is carefully clarified. Experimentally, joint time-frequency analysis for a variety of ultrafast non-stationary RF signals is demonstrated, where dynamic frequency resolution of 60 MHz, dynamic observation bandwidth of 1.98 GHz and acquisition frame rate of 160 MHz are simultaneously realized. The scheme we proposed is promising for the dynamic spectrum monitoring of broadband non-stationary RF signals.
A Hybrid CNN-CRF Inference Models for 3D Mesh Segmentation

Owing to the wide spread of the 3D objects technologies, learning 3D objects labeling and segmentation is becoming one of the most provocative tasks in computer vision and digital multimedia. Recently, convolutional neural network (CNN) has proved itself as a powerful model in segmentation and classification by giving excellent performances. The use of a graphical model such as conditional random field (CRF) contributes further in capturing contextual information and thus improving the segmentation performance. In this paper, we implement a deep architecture in order to segment and label 3D shape parts by considering both spectral and geometric features via a combined framework consisting of a CNN and CRF models. First, low-level features are used to learn deep features using a CNN model, and then formulate the deep CRF model with a CNN-based unary and pairwise potential functions to effectively extract the semantic correlations between adjacent triangles on the mesh. By comparing our results with those from several state-of-the-art, our method shows promising potentials.
Using mobile technology for reading assessment

The enormous potential of Information and Communication Technologies (ICT) for addressing critical educational issues is generally acknowledged, but its use in the assessment of the complex skills of reading and understanding a text has been very limited to date. The paper contrasts traditional reading assessment protocols with ReadLet, an ICT platform with a tablet front-end, designed to support online monitoring of silent and oral reading abilities in early graders. ReadLet makes use of cloud computing and mobile technology for large-scale data collection and allows the time alignment of the child's reading behaviour with texts tagged using Natural Language Processing (NLP) tools. Initial findings replicate established benchmarks from the psycholinguistic literature on reading in both typically and atypically developing children, making the application a new ground-breaking approach in the evaluation of reading skills.
Study of Asphaltene Precipitation During CO2 Injection to Oil Reservoirs in the Presence of Iron Oxide Nanoparticles by Interfacial Tension and Bond Number Measurements

CO2 injection is one of the most frequently used enhanced oil recovery methods; however, it causes asphaltene precipitation in porous media and wellbore and wellhead facilities. Carbon dioxide saturated with nanoparticles can be used to enhance oil recovery with lower asphaltene precipitation issues. In this study, the vanishing interfacial tension technique was used to investigate the possibility of diminishing asphaltene precipitation by nanoparticles. The interfacial tension (IFT) of synthetic oil/carbon dioxide was measured using the pendant drop method. The results illustrated that, for synthetic oil samples containing asphaltene, the IFT data versus pressure decrease linearly with two different slopes at lowand high-pressure ranges. At high pressures, the slope of the plot is lower than the one in the low-pressure range. The addition of iron oxide nanoparticles to the oil solution reduces the interfacial tension at higher pressures with a steeper slope, showing that nanoparticles can decrease asphaltene precipitation. The plot of Bond number versus pressure also confirmed the impact of nanoparticles on reducing asphaltene precipitation. In terms of the temperature effect, the presence of nanoparticles at 50 °C resulted in a 16.34% reduction in asphaltene precipitation and a 19.65% reduction at 70 °C. The minimum miscibility pressure changed from 10.17 to 30.96 MPa at 70 °C; however, in the presence of nanoparticles, it reduced from 10.06 to 16.56. Therefore, the technique introduced in this study could be applied to avoid the problems associated with altering the gas injection mode from miscible to immiscible.
Metal–organic framework MOF-199-catalyzed direct and one-pot synthesis of thiols, sulfides and disulfides from aryl halides in wet polyethylene glycols (PEG 400)

ABSTRACT A highly porous metal–organic frame work Cu3 BTC2 (copper(II)-benzene-1,3,5-tricarboxylate) that is known as MOF-199 was synthesized from the reaction of 1,3,5-benzenetricarboxylic acid and Cu(OAc)2·H2O by a solvothermal method and characterized by several techniques including FT-IR, XRD, EDX and scanning electron microscopy. The MOF-199 used as an efficient catalyst for one-pot synthesis of thiols by domino reactions of aryl halides and thiourea, and subsequently conversion to aryl alkyl sulfides and diaryl disulfides in polyethylene glycols (PEGs). A variety of aryl alkyl sulfides can be obtained in good to excellent yields in a relatively short reaction time and in the presence of the trace amount of catalyst. Also, the catalyst can be separated from the reaction mixture by decanting, and be reused without significant degradation in catalytic activity. GRAPHICAL ABSTRACT
Organic and Third Phase in HNO3/TBP/n-Dodecane System: No Reverse Micelles

ABSTRACT The composition and speciation of the organic and third phases in the system HNO3/TBP (tri-n-butyl phosphate)/n-dodecane have been examined by a combination of gravimetric, Karl Fischer analysis, chemical analysis, FTIR, and 31P NMR spectroscopy, with particular emphasis on the transition from the two-phase to the three-phase region. Phase densities indicate that third-phase formation takes place for initial aqueous HNO3 concentrations above 15 M, while the results from the stoichiometric analysis imply that the organic and third phases are characterized by two distinct species, namely the mono-solvate TBP⋅HNO3 and the hemi-solvate TBP⋅2HNO3, respectively. Furthermore, the 31P NMR spectra of organic and third phase show no significant chemical differences at the phosphorus centers, suggesting that the second HNO3 molecule in the third phase is bound to HNO3 rather than TBP. The third-phase FTIR spectra reveal stronger vibrational absorption bands at 1028, 1310, 1653, and 3200–3500 cm−1, reflecting higher concentrations of H2O, HNO3, and TBP. The molecular dynamics simulation data predict structures in accord with the spectroscopically identified speciation, indicating inequivalent HNO3 molecules in the third phase. The predicted structures of the organic and third phases are more akin to microemulsion networks rather than the distinct, reverse micelles assumed in previous studies. H2O appears to be present as a disordered hydrogen-bonded solvate stabilizing the polar TBP/HNO3 aggregates in the organic matrix, and not as a strongly bound hydrate species in aggregates with defined stoichiometry.