Miracle-dz/UniFAR-FTUs huggingface dataset:
ITEC-WP 10 D 10 . 4-SUPPORT FOR IMPLEMENTING ITEC ENGAGING SCENARIOS V 4

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Data Centric Security Approach : A way to Cloud Computing Security & Privacy

Cloud computing paradigms are gaining widespread acceptance due to the various benefits they offer. These include cost-effectiveness, time savings and efficient utilization of computing resources. However, privacy and security issues are among the major obstacles holding back the widespread adoption of this new technology. Some research is focused on improving the security at the application, operating system, Virtual Machine (VM) or hardware levels. These solutions do not normally provide a comprehensive solution and they still keep the data security measures under the control of the cloud provider. Another direction of research is based on Trust Computing (TC) concepts. In essence, these provide a set of trusted third party technologies to secure the VM from the cloud provider. While these approaches provide the users with tools to monitor and assess the security aspects of their data, they do not provide the users with much control capability. In contrast, Data Centric Security (DCS) is an emerging approach that aims to provide data owners with full control of their data security from within the data itself, throughout the data’s lifecycle on the cloud. However, the concept of the DCS approach is interpreted in various ways in the literature and there is not yet a standardized framework of applying this approach to the cloud model.
About The Properties Of A Hidden Matter

Annotation: A new approach to the study of the properties of the hidden mass of the universe is proposed, based on the modification of the law of universal gravitation with respect to continuous media. According to him, gravity is a consequence of the inhomogeneous distribution of the density of matter in the universe. This law reveals the presence of "strong" gravity in hidden matter, which exceeds the Newtonian potential on the surface of the Sun by five orders of magnitude, as well as the existence of gravitational equilibrium and gravitational repulsive forces that make "dark energy" an unnecessary entity. The possibility of separating the "free" (workable) part in the gravitational energy and its division into "gravistatic" and "gravikinetic" components is revealed. It is shown that this part of the gravitational energy makes the hidden matter the true "fuel" of the stars and the cause of many phenomena that seem to contradict the laws of physics. At the same time, it is shown that self-oscillations of density inevitably arise in hidden matter, transforming part of its gravitational energy into other forms and making it the "first principle" of all forms of baryonic (visible) matter and a self-sufficient carrier of light. Along with the justification of these properties of hidden matter and their experimental confirmation, an explanation is given of a number of observable cosmological phenomena.
Zebrafish Kit ligands cooperate with erythropoietin to promote erythroid cell expansion

Kit ligand (Kitlg) is pleiotropic cytokine with a prominent role in vertebrate erythropoiesis. Although the role of Kitlg in this process has not yet been reported in Danio rerio (zebrafish), in the present study, we show that its function is evolutionary conserved. Zebrafish possess two copies of Kitlg genes (Kitlga and Kitlgb) due to whole genome duplication. To determine the role of each ligand in zebrafish, we performed a series of ex vivo and in vivo gain- and loss-of-function experiments. First, we tested the biological activity of recombinant Kitlg proteins in suspension culture from zebrafish whole kidney marrow and we demonstrate that Kitlga is necessary for expansion of erythroid progenitors ex vivo. To further address the role of kitlga and kitlgb in hematopoietic development in vivo, we performed gain-of-function experiments in zebrafish embryos, showing that both ligands cooperate with erythropoietin (Epo) to promote erythroid cell expansion. Finally, using the kita mutant (kitab5/b5 or sparse), we show that Kita receptor is crucial for Kitlga/b cooperation with Epo in erythroid cells. In summary, using optimized suspension culture conditions with recombinant cytokines (Epo, Kitlga), we are reporting for the first time ex vivo suspension cultures of zebrafish hematopoietic progenitor cells, which can serve as an indispensable tool to study normal and aberrant hematopoiesis in zebrafish. Furthermore, we conclude that although partial functional diversification of Kit ligands has been described in other processes, in erythroid development, both paralogs play a similar role and their function is evolutionary conserved. Key points: Kit signaling contributes to erythroid cell development and is conserved from fish to man Ex vivo expansion and self-renewal of zebrafish erythroid progenitors requires addition of recombinant Kitlga
Multipole magnets for the HIAF fragment separator using the Canted-Cosine-Theta (CCT) geometry

The fragment separator of the HIAF (High Intensity Heavy Ion Accelerator Facility) project called HFRS requires quadrupoles with high gradients (11.4 T/m) and large bores (320 mm in diameter). The iron dominated magnets with superconducting coils have been widely used in the similar facilities such as A1900, BigRIPS, Super! FRS and RISP with the advantages of low request for coils installation precision, simple fabrication and low cost, but they have large cold mass and helium containment, which result in long time cooling down and high pressure rise during a quench. In addition, due to iron saturation, it is hard to guarantee on the field quality in the operated field range. A new coil dominated design based on the Canted! Cosine! Theta geometry is presented for HFRS, which is expected to overcome these problems. The design superimposes several layers of oppositely wound helical windings to generate high quality quadrupole. Sextupole, octupole and steering dipole can also be easily integrated to reduce the length of cryostat. This paper reports the detailed design of HFRS multiplets based on the CCT concept and the construction of a subscale prototype.
Optimized FWM Parameters for FTTH Using DWDM Network

A DWDM System consisting of transmitter, optical span and receiver is designed. The line coding technique NRZ (Non Return To Zero) has been used as the modulation schemes. The variation in the four wave mixing is analyzed with respect to the designed DWDM (Dense Wavelength Division Multiplexing) system. The DWDM is designed and simulated on Optisystem and their BER (Bit Error Rate) is calculated. The DWDM system is implemented in a FTTH (Fiber To The Home) system and simulated on Optisystem and their BER is calculated.
A dual-grid dual-phase strategy for constrained multi-objective optimization

Constrained multi-objective optimization problems (CMOPs) appear frequently in engineering applications. In some cases, feasible regions are narrow and/or disconnected. For this kind of problems, existing constraint-handling methods, integrated with multi-objective evolutionary algorithms, are easily stuck at local optima. Aiming to strengthen the global search ability, a dual-grid dual-phase strategy is proposed, which is termed dual-grid push and pull search (DPPS). In the DPPS, two populations, corresponding to dual grids, are used individually to explore the feasible and infeasible spaces. Specifically, one population maintains feasible solutions, and the other explores the whole search space without considering constraints. Then, the two populations share useful information and pull each other so as to enable the algorithm to search for the optimal feasible region (i.e., Pareto solution set). To demonstrate the effectiveness of the proposed algorithm, the MOEA/D integrated DPPS (MOEA/D-DPPS) is tested on a frequently-used benchmark suite as well as a newly-constructed suite. Experimental results clearly show the superiority of MOEA/D-DPPS compared with six state-of-the-art algorithms.
Textured PDMS Films Applied to Thin Crystalline Silicon Solar Cells

Front surface texturization is a standard procedure used to improve optical properties of photovoltaic devices. In some particular cases, such as when dealing with ultrathin substrates, common texturization techniques can become unpractical or even unfeasible. Texturized polymer films applied on top of such devices may be used as an alternative. In this article, we report on the development of textured polydimethylsiloxane (PDMS) films to be placed on top of planar crystalline silicon solar cells based on thin substrates (≤40 μm). The PDMS polymer is deposited onto a rough surface (conventional random pyramid textured silicon), cured and detached from it. By scanning electron microscope images, we demonstrate that the dilution of PDMS into toluene helps in a better replica of the master surface. Next, we apply the optimized PDMS films on top of dummy samples based on 10, 20, and 40 μm thick crystalline silicon (c-Si) substrates whose reflectance is significantly reduced after placing the PDMS films. Accurate optical simulations indicate that the optical improvement comes from three mechanisms: higher light transmission into the device, lower reflectance at the c-Si surface, and better light trapping properties at the thin c-Si absorber. Experimental verification of the optical improvement with texturized PDMS films is reported based on 40 μm thick solar cell, where a short-circuit current density gain of 1.7 mA/cm2 is observed.
Neural-Network-based Finite-Set Model Predictive Control of an Autonomous Surface Vehicle Powered by an Electrical Motor

This paper is dedicated to a problem of surge speed control for an autonomous surface vehicle (ASV) powered by an electrical motor. The surge dynamics, propeller model, and motor model are unknown. A surge speed controller is developed based on a finite-set model predictive control and a neural predictor design. Firstly, two predictors based on neural networks are developed to estimate the unknown nonlinear functions existing in electrical motor model, propeller model and surge dynamics. The stability analysis is provided on the basis of input-to-state stability (ISS) theory. Then, a model predictive control scheme is proposed for surge speed control with a possible finite voltage control set and a predefined cost function. The simulation results are provided to illustrate the validity of the proposed surge velocity controller for the ASV.
Dual Frequency Buck-Boost Interleaved Inverter for All Metal Induction Heating Applications

Multiple load induction heating applications require good control techniques and high power inverters. A dual frequency buck-boost inverter configuration for different loads operating at different frequencies is proposed in this paper. Each load uses one half-bridge series resonant inverter. Effective input voltage to each half-bridge becomes 2VDC in this configuration and hence it handles same power as that of full-bridge topology. Through buck-boost converter half of the load power is supplied to each load and remaining half load power is transferred directly from the source. With ADC control, each load power is controlled independently. This topology uses less number of components. The presented inverter configuration is simulated with two loads and can be extended to multiple loads also.
Rate Analysis For Offline Simulation Online Application

We consider a recently proposed simulation-based decision-making framework, called offline-simulation-online-application (OSOA). In this framework, simulation experiments are not performed after the target problem is set up with all the input parameters; instead, they are performed before that with all the possible parameters that might come up in the target problem. Then, these computational results are directly used in real time for system evaluation or system optimization when the input parameters of the target problem are known. In this paper, we follow this framework and use stochastic kriging (SK) to model the system performance from the covariate space. Two measures, namely IMSE and IPFS, are proposed to evaluate the prediction errors for system evaluation and system optimization respectively. We establish the convergence rates of these two measures. They quantify the magnitude of prediction errors for the online application after a certain period of time is spent for the offline simulation.
3-D Parallel Simulations of Streamer Discharges in Air Considering Photoionization

We perform the 3-D parallel simulations of the streamer discharges in air using the minimal fluid model considering the photoionization. The SP3 photoionization model, which consists of a series of elliptic equations with coupled boundary conditions, is solved using an alternating iteration method, which separates the coupled elliptic equations into independent equations; during each alternating iteration, a geometric multigrid-preconditioned flexible generalized minimal residual method (FGMRES) solver is used to efficiently solve the elliptic equation in the photoionization model. It is numerically shown that the proposed photoionization solver typically converges to a relative residual of 10−6 with two to four alternating iterations and has a very good parallel efficiency. The interaction of two double-headed streamers is studied considering the photoionization, using 1000 CPU cores and more than 2 billion mesh cells.
Detection of Arc Faults in PV Systems Using Compressed Sensing

As photovoltaic systems grow in size, there has been an increasing desire to automate the detection of arc faults. Any automated system for arc detection must be as fast and accurate as possible: delayed detection of electrical arcs can lead to fire and considerable system damage, while false positives that cause preventative system shutdown are associated with a significant financial cost. In this article, we present a novel approach to detect arcs in dc microgrids via their high-frequency (HF) spectral pattern using ideas from compressed sensing. The acquisition and analysis of HF signals using analog-to-digital converter technology typically requires costly hardware and is not feasible for on-site installation at power plants. However, sparsifying the signal by filtering everything but a narrow HF band enables the use of a modulated wideband converter to sample the arc signature at sub-Nyquist frequencies. We then calculate a characteristic band power within the selected spectrum slice over time and show that it can be used to reliably detect arc events via simple thresholding. We have evaluated our methods on both simulated and experimentally generated arc signals. Finally, we perform statistical analysis of power distributions using linear discriminant analysis in order to identify the frequency range best suited for arc detection.
Implementation of FreeRTOS based Precision Time Protocol (PTP) application as per IEEE1588v2 standards for Xilinx Zynq UltraScale Plus MPSoC devices

This work proposes a method for the implementation of PTPd (Precision Time Protocol deamon) with the Gigabit Ethernet Module (GEM) Interface for test devices. The programmable real-time clock and timestamp unit was implemented in the programmable logic to achieve the synchronization accuracy of sub-microsecond. PTPd has been reconfigured and implanted into a FreeRTOS operating system to create a PTP state machine and the IEEE1588 IP core software driver has been created to give the application layer access to the precise timestamp in the link layer. This paper evaluates in detail the matter of the IEEE 1588 standard and provides a “Xilinx ZynqMP UltraScale plus SoC + MAC + PHY” technique, a hardware solution for stamping the arrival and departure period of PTP packets. Where packets are obtained between MAC and PHY layers from Media Independent Interface (MII). The result indicates that the solution can detect the messages transmit and receipt for synchronization accurately.
Joint Distribution Learning in the Framework of Variational Autoencoders for Far-Field Speech Enhancement

Far-field speech recognition is a challenging task as speech recognizers trained on close-talk speech do not generalize well to far-field speech. In order to handle such issues, neural network based speech enhancement is typically applied using denoising autoencoder (DA). Recently generative models have become more popular particularly in the field of image generation and translation. One of the popular techniques in this generative framework is variational autoencoder (VAE). In this paper we consider VAE for speech enhancement task in the context of automatic speech recognition (ASR). We propose a novel modification in the conventional VAE to model joint distribution of the far-field and close-talk features for a common latent space representation, which we refer to as joint-VAE. Unlike conventional VAE, joint-VAE involves one encoder network that projects the far-field features onto a latent space and two decoder networks that generate close-talk and far-field features separately. Experiments conducted on the AMI corpus show that it gives a relative WER improvement of 9% compared to conventional DA and a relative improvement of 19.2% compared to mismatched train and test scenario.
Building Detection from LIDAR Point Cloud Data

LiDAR (Light Detection and Ranging) is an emerging technology now and has proved to be one of the best techniques for 3D city modeling. Building detection is an important aspect of 3D city modeling as it can help in urban planning, utility services, disaster management, traffic management, environmental monitoring and many other applications. In this paper we propose a method in which building structures can be accurately discriminated from vegetation. Pre-processing of the data is done using a remote sensing tool called Las Tools. The data is structured using kd tree and then further segmented using Euclidean distance clustering. Then we process this data using another open-source remote sensing tool called CloudCompare. This paper will help in imparting a clear idea of how efficiently and accurately building detection can be performed with the help of these open-source tools without deploying much complex algorithms.
A Wideband Tunable Power Divider for SWIPT Systems

A two-way tunable power divider for Simultaneous Wireless Information and Power Transfer (SWIPT) is proposed in this paper. The power divider divides the incoming power in such a way that maximum power is utilized for energy harvesting purposes and the rest of the power is used for information decoding purposes. This unequal distribution of power is realized by tuning the varactor diode’s reverse biasing voltages. A good matching performance is attained using the radial and short stubs at the input and one of the output ports, respectively. High isolation is achieved with the help of the resistor used for connecting the output ports of the power divider. The achieved power division ratios vary from 13:1 to 28:1. The tunable power divider is designed and fabricated at 2.4 GHz. The bandwidth measured at 10 dB return loss is 3.2 GHz and the isolation better than 12 dB is achieved between the output ports. The designed structure is compact and good consistency is observed between the simulated and measured results. The designed power divider may be used for future 5G wireless networks.
The Activity-Entity-Impact Method: Understanding Bottleneck Behavior of Simulation Models Demonstrated by an Emergency Department Model

Simulation models are often used to gain a better understanding of a system’s sensitivity to changes in the input parameters. Data gathered during simulation runs is aggregated to Key Performance Indicators (KPIs) that allow one to assess a model’s or system’s performance. KPIs do not provide a deeper understanding of the causes of the observed output because this is not their primary objective. By contrast, dynamic bottleneck methods both identify elements that yield the largest gain in productivity with increased availability and also visualize these elements over time to enable bottlenecks to be better understood. In this paper we discuss whether dynamic bottleneck detection methods can be utilized to identify, measure, and visualize causes of observed behavior in complex models. We extend standard bottleneck detection methods, and introduce the Activity-Entity-Impact-Method. The practicality of the method is demonstrated by an example model of a typical Emergency Department setting.
Security Vulnerabilities in Applying Decentralized Ledger Systems for Obfuscating Hardwares

Security in daily transactions, not only in the financial sector, but also in various upcoming Industrial smart application areas needs a generic solution, out of the cat and mouse race, where frequently vulnerabilities are pointed out and a quick patch is fabricated to resolve the issue temporarily. An impromptu solution to this protracted issue will not be enough to solve on the long run, thus dedicated researchers have been putting efforts to their best for finding the real problem by asking the right questions. Through this paper authors have attempted to trace the current issues in handling decentralised ledger system using blockchain technology and discussed state of the art management in auditing hardware obfuscation techniques.
A Simple Cluster Head Selection Technique of Wireless Sensor Networks

For extending lifespan, significant energy saving for cluster is a problem of Wireless SensorNetworks (WSN). Properly Cluster Heads (CHs) selection is a resolution to overcome this problem. In this work, we have described a simple CH selection method that will save substantial energy of nodes as well as increase lifespan of the network. Proposed technique considered remaining Energy, Neighbor information, Distance between CHs and Base Station (BS) and One hop neighbor information. Moreover, we have considered some nodes to send data directly to BS other than CH and dynamically distance adjustment for each round which will save much energy of the network. Proposed protocol will save significant energy by reducing back transmission in a stable manner. We have simulated offered protocol and compared with LEACH-C and An Efficient Cluster Head Selection (ECHS). We found major improvement of performance with respect to First Node Dai (1ND), Last Node Death (END); energy consumption in each rounds, and total packet send to BS as throughput.