Miracle-dz/UniFAR-FTUs huggingface dataset:
Realization of SiOx/SiNx Stacks as Multi Anti-Reflection Coatings and Selectively Copper-plating Mask For Silicon Heterojunction Solar Cell With 23.5% Efficiency

${\mathrm{SiO_{x}/SiN_{x}/IWO}}$ stacks were fabricated as multi anti-reflection coatings and applied as in suit deposited plating mask for SHJ solar cells. The optical-electrical properties of $\mathrm{SiO_{x}/SiN_{x}/IWO}$ stacks were investigated. The average reflectance with 90 nm SiOx/ 30 nm SiNx/ 60 nm IWO stacks reduced at 300-1200 nm wavelength, leading to increased external quantum efficiency response and a Jsc gain of 1.16 mA/cm2 and an improved efficiency of 23.52%. Meanwhile, copper plated process was applied. The surface of screen printed finger is rough, with lots of voids in the size of hundreds nanometers and silver particles, making the surface area of finger much larger than textured silicon and SiOx/SiNx stacks could not cover finger surface completely with relative low thickness. Besides, the organic solvent in the paste volatilize and the silver particles merge with each other during the annealing process, which enables silver paste penetrating through SiOx coating to form good ohmic contact. Then, $\mathrm{SiO_{x}/SiN_{x}}$ stacks were used as plating mask for copper plating of SHJ solar cells and showing promising application for mass production.
Coverage-Improvement of V2I Communication Through Car-Relays in Microcellular Urban Networks

In this paper, we consider a microcellular urban network, where micro-cells provide a wireless connection to vehicular users. We focus on vehicular relaying to enhance the quality of the V2I link and therefore to improve the overall coverage in the network. To quantify the coverage gain, we compare the performance of direct communication between microcell and vehicular user with the relay-aided communication. In the examined scenario, we create a Manhattan grid of streets where in each street micro-cell base stations and vehicular users are randomly placed according to a Poisson point process. The employed pathloss distinguishes whether the transmitter is in the same street as the receiver, in a crossing or in a parallel street. We investigate our model analytically by leveraging tools from stochastic geometry as well as by Monte Carlo system level simulations. We compare results for the relay-assisted link and the direct link depending on the user density in terms of pathloss, SINR and coverage.
Development of a Micro-Turbojet Test Rig for Investigating Effects of Alternative Fuel

The goal of the present paper is to describe a turbojet test bench dedicated to investigate the effect of alternative fuels on the operational parameters of a gas turbine engine. Aviation uses significant amounts of fuel including commercial as well as military applications. Due to environment concerns and possible shortage of fossil fuel sources, the engine developers have considered alternative fuels already from the 1980’s. Though the above mentioned problems constantly emerge nowadays there is no mature technology that could be used widely. Therefore intensive research of the problem is still up-to-date. The main intent of the authors is to focus on the establishment of a data acquisition system, which can reveal the differences in operational parameters of the turbojet engine if the type of fuel is changed.
Metabolic Reprogramming of Non-Hodgkin's B-Cell Lymphomas and Potential Therapeutic Strategies

Metabolism is a wide and general term that refers to any intracellular pathways the cell utilizes in order to satisfy its energetic demand and to support cell viability and/or division. Along with phenotypic changes, all mammalian cells including immune cells modulate their metabolic program in order to reach their effector functions. Exacerbated metabolism and metabolic flexibility are also hallmarks of tumor initiation and of tumor cell progression in a complex tumor microenvironment. Metabolic reprogramming is mainly directed by the serine/threonine kinase mTOR (mammalian target of rapamycin). mTOR exists in two structurally and functionally distinct complexes, mTORC1 and mTORC2 that coordinate environmental signals and metabolic/anabolic pathways to provide macromolecules and energy needed for survival and growth. Activation of mTORC1 is required during development, differentiation and activation of immune cells. Aberrant and persistent activation of mTORC1 is often observed in malignant B cells such as Non-Hodgkin's (NH) B-cell lymphomas. Here, we review recent insights on cell metabolism and on basic mechanisms of mTORC1 regulation and metabolic functions. We highlight the distinct mechanisms driving mTORC1 activation in the three most-common types of NH B-cell lymphomas (Diffuse Large B Cell Lymphomas, Follicular Lymphomas, and Mantle Cell Lymphomas), for which the first generation of mTORC1 inhibitors (rapalogs) have been extensively evaluated in preclinical and clinical settings. Finally, we discuss the reasons for limited clinical success of this therapy and focus on potential therapeutic strategies targeting metabolic pathways, upstream and downstream of mTORC1, that can be combined to rapalogs in order to improve patient's outcome.
The Broken-Heart Printed Antenna for Ultrawideband Applications: Design and Characteristics Analysis

A compact, slotted partial ground, broken-heart-shaped microstrip patch antenna intended for use in ultrawideband (UWB) applications is presented. The antenna is composed of a broken-heart-shaped patch and slotted partial ground plane. The antenna has an electrical dimension of 0.29&lambda; &times; 0.17&lambda; at the lowest operating frequency of 2.90 GHz. The finite element method (FEM)-based high-frequency structural simulator (HFSS) and the time-domain-method-based Computer Simulation Technology (CST) Microwave Studio simulator have been used to simulate the presented antenna. The antenna was measured after prototype fabrication. The antenna covers the bandwidth from 2.90 to 10.70 GHz. The maximum gain of the presented antenna is 5.3 dBi with a notable efficiency of 86.6%. The fidelity factor for faceto-face and side-by-side orientation of the antenna is ~79% and 80%, respectively. The impedance bandwidth of the presented antenna is wide enough to be used in UWB wireless communications as well as microwave imaging and UWB radar applications.
Analysis of Starting Characteristics of Plunger Pump Driven by Brushless DC Motor

By analyzing the structure and theory of plunger pump hydraulic system driven by brushless DC motor, the speed of motor and pressure of the hydraulic system are studied in the paper. The rise time of the motor speed is almost the same with load flow of liquid changed. But the rise time of the pressure extends with load flow increasing. At the starting process, the power of the load is very high because of the accumulator and pipelines. The experimental results show the process with different flow of liquid.
Generic calibration of cameras with non-parallel optical elements

Multiple cameras are increasingly prevalent for autonomous driving, and the increase need to have 360 degree perception of world space has led to the combination of various cameras in the varieties of narrow-angle and wide-angle field of view. This has led to issues regarding the quality of these optics as a result of bad and cheap designs. Intrinsic calibration is indispensable for accurate perception of the environment in order for it to make accurate decisions such as camera pose estimation and 3-D reconstruction. In this work, we propose a lens distortion model that has been motivated by unintentional tilt in the optical lens system. The proposed distortion model has been added to current state of art generic method of Kannala to form an extended model. To our knowledge, this is the first time that the idea of tilt distortion has been introduced for wide-angle view and fish-eye cameras. We show improved result of 4 to 13% from experiments.
SELECTION AND RECOGNITION OF THE SPECIFIED RADIO SIGNALS IN THE SW BAND

Проблематика. В настоящее время беспроводные радиотехнологии являются интенсивно развивающейся отраслью телекоммуникационной индустрии, что обуславливается их высокой популярностью вследствие удобства их использования для гражданского и специализированного применения. В настоящее время частотный ресурс уже достаточно перегружен, что приводит к проблемам электромагнитной совместимости. Решить эту проблему возможно путем эффективного использования частотного ресурса, для этих целей производится контроль за использованием радиочастотного ресурса путем автоматизированного радиомониторинга. Сейчас в эфире работает множество радиоэлектронных средств и их количество стремительно возрастает с каждым днём, что может привести к тому, что на обработку могут попасть не только известны радиосигналы, но и неизвестные сигналы, что в свою очередь может привести к ошибкам распознавания. В данной работе исследуются алгоритмы селекции и распознавания заданных радиосигналов, которые учитывают класс неизвестных сигналов. Цель исследований. Целью работы является исследование показазателей качества алгоритмов селекции и распознавания заданных радиосигналов при наличии неизвестных сигналов во время радиомониторинга в КВ диапазоне. Методика реализации. Исследование алгоритмов селекции и распознавания заданных радиосигналов при наличии неизвестных сигналов методом имитационного моделирования на выборках реальных сигналов. Результаты исследований. Получены значения показателей качества селекции и распознавания заданных радиосигналов при наличии неизвестных сигналов, которые есть приемлемыми для практики радиомониторинга. Предложенные алгоритмы распознавания должны повысить качество результатов радиомониторинга, и тем самым улучшить результаты проведения радимониторинга. Выводы. Предложеннные алгоритмы селекции и распознавания заданных радиосигналов при наличии неизвестных сигналов позволят повысить качество радиомониторинга в КВ диапазоне.
Importance of Nanocrystallites in a-Si:H Passivation Layer in Improving The Performance of Silicon Heterojunction Solar Cells

Correlation between surface passivation of crystalline silicon and the microstructure of silicon passivation layer has been investigated. Based on the optical constants determined by Spectroscopic Ellipsometry measurements, effective medium approximations has been employed to simulate the microstructure of silicon thin film with the mixed phase, including amorphous structure and spherical or ellipsoidal crystallites. A key factorfc, describes the volume fraction of nanocrystallites in the amorphous network, has a significant role to improve the fill factor of silicon heterojunction solar cells. Moreover, the cell performance can be improved by the increasing material density of intrinsic silicon interface layer.
Wireless Signal Strength Analysis in a Home Network

With the advert, invention of wireless fidelity commonly called as Wi-Fi in the field of communication and computer networks a new era or revolution has taken place. Many studies have been conducted on the Wi-Fi signal and their characteristics also methods to increase security and to establish a secure connection in a wireless network has been studied in great detail. Also in path research have been carried out to increase throughput, data transfer rate and Wi-Fi signal strength. In this paper the analysis of different Wireless Local Area Network [WLAN] surrounding the home network using different tools is done. Also an author created a map of area in an app called as heat mapper, specified Access points, after which the dead zones and range was analyzed. Also, Wi-Fi monitor and Wi-Fi analyzer was used to analyze the signal strength and plot time graph and give information about mac address, IP address, security used etc. Authors analyzed the downlink and uplink speed graph and different methods to increase or boost signal strength.
Integrating Brillouin processing with functional circuits for enhanced RF photonic processing

On-chip linear and nonlinear optical effects have shown tremendous potentials for applications in RF photonic signal processing. Combining their complementary optical properties in the same integrated platform is expected to satisfy the future increasing demands of high-performance integrated microwave photonic systems. However, the integration of linear circuits with high-performance optical nonlinearity elements remains challenging. Here, we report the first proof-of-concept demonstration of a microwave photonic notch filter based on the simultaneous integration of active Brillouin circuits and passive ring resonators on the same photonic chip, merging advanced filtering functionality, optimized performance and compactness.
Design and Implementation of Neural Network Based Non Linear Control System (LQR) for Target Tracking Mobile Robots

This research work involves the speed control of a mobile robot where stabilization is provided by Non-linear controller. A Mobile Robot capable of following human target, assisted by various sensors that detects the clearance distance between the target and the robot to avoid collision or to maintain constant distance needs a robust control system. A robot in order to follow a human or target which has variable speed must have decision capabilities to decide when to speed up or slow down according to the situation. This decision can be obtained by the use of Artificial Neural Network (ANN) which reduces the burden on the controller reducing the complexity of calculation involved to control the speed of the motors. All these above sensors and actuators provide values as input to the Neural Network database for learning stage providing classification into several actions. The classes and weights obtained by the Neural Network learning phase is then used to vary the speed of the Robot. The speed however being unstable and providing several unnecessary movements will then be stabilized by using Linear Quadratic Regulator control algorithm. Thus, providing a complete solution to setting a fluent and stable Mobile Robot that can track and follow and target under any conditions.
Online Graph-Adaptive Learning With Scalability and Privacy

Graphs are widely adopted for modeling complex systems, including financial, biological, and social networks. Nodes in networks usually entail attributes, such as the age or gender of users in a social network. However, real-world networks can have very large size, and nodal attributes can be unavailable to a number of nodes, e.g., due to privacy concerns. Moreover, new nodes can emerge over time, which can necessitate real-time evaluation of their nodal attributes. In this context, this paper deals with scalable learning of nodal attributes by estimating a nodal function based on noisy observations at a subset of nodes. A multikernel-based approach is developed, which is scalable to large-size networks. Unlike most existing methods that re-solve the function estimation problem over all existing nodes whenever a new node joins the network, the novel method is capable of providing real-time evaluation of the function values on newly joining nodes without resorting to a batch solver. Interestingly, the novel scheme only relies on an encrypted version of each node's connectivity in order to learn the nodal attributes, which promotes privacy. Experiments on both synthetic and real datasets corroborate the effectiveness of the proposed methods.
Evaluation of diffused phosphorus emitters using Griddler-PC1D

Griddler-PC1D is an integrated solar cell simulation platform which combines the accurate solutions of recombination and photo-generated carrier collection in diffused emitters by cmd-PC1D 6–2, with the ability of the finite-element simulator Griddler to solve the I-V characteristics of a complete solar cell. With this approach, both the presence of lateral currents in the emitter and base layers, as well as different recombination current densities under the various passivated and metallized regions can be taken into account. The advent of Griddler AI further aids the extraction of recombination under the metal contacts, by analysis of photoluminescence images of easy-toprepare test structures. In this work, we detail the use of Griddler-PC1D to investigate the effectiveness of a series of phosphorus emitters, by reconciling experimentally determined emitter saturation current densities (J0e) with simulation, predicting metal-induced recombination, and performing automated metal grid optimization.
Deep Learning-Based Segmentation for the Extraction of Micro-Doppler Signatures

We present a method for extracting micro-Doppler signatures using a deep convolutional neural network that learns to identify and separate relevant micro-Doppler components from the background. A modified convolutional neural network (fully convolutional network) is trained end-to-end to perform dense predictions from the micro-Doppler signature at the input, generating a map with labels on a pixel level at the output. The network learns intermediate representations with the characteristic patterns of the micro-Doppler paths generated by individual scatterers and is capable of identifying and locating them in the time-frequency representation. The model trained on a simulated environment shows very good performance metrics even in noisy environments, and the experimental results with a continuous wave (CW) radar at 24 GHz indicates that the model can be applied to real scenarios. Moreover, the method scales properly to more complex signatures when several components are superimposed in the time-frequency representation, which indicates that this concept might represent a promising approach for interpreting complex micro-Doppler signatures.
Effect of Tuning Parameter on the Stability of the TDF-IMC Scheme for Load Frequency Control

Effect of tuning parameter on the stability of the TDF-IMC for load frequency control is studied. Choice of an optimal value is found to be directly affecting the feedback filter $(\mathbf{Q}_{\mathbf{d}})$ and depends on the nature of model order reduction scheme used (such as Padé approximation, Routh and SOPDT). The findings corroborate with our previously published results, that the bi-parametric variation in $(\mathbf{T}_{\mathbf{g}}-\mathbf{T}_{\mathbf{t}})$ can be effectively mitigated by preferring SOPDT in comparison to Pade and Routh for an optimal tuning parameter. Further, the response to disturbance is quick and damps swiftly with low amplitude oscillations. In conclusion, we identify that the SOPDT offers better performance at optimal tuning parameter (depending on the design preference for the gain and phase margin).
Load Balancing through Block Rearrangement Policy for Hadoop Heterogeneous Cluster

To store and analyze Big Data, Hadoop is the most common tool for the researchers and scientists. The storage of huge amount of data in Hadoop is done using Hadoop Distributed File System (HDFS). HDFS uses block placement policy to split a very large file into blocks and place them across the cluster in a distributed manner. Basically, Hadoop and HDFS have been designed in such a way that it works efficiently on the homogeneous cluster. But in this era of networking, we cannot imagine having a cluster of homogeneous nodes only. So, there is the need of storage policy that can work efficiently on both homogeneous as well as the heterogeneous cluster. Thus, the needs of applications that can be executed time-efficiently based on homogeneous as well as the heterogeneous environment can be sufficed. Data locality in Hadoop maps the data block to process in the same node, but often when you're dealing with Big Data, it is required to map the data block to the processes across multiple nodes. To deal with this Hadoop has functionality to copy the data block where mappers are running. This creates a lot of performance degradation especially on heterogeneous cluster due to I/O delay or network congestions. Here we present a Novel algorithm to balance the data blocks on specific nodes (i.e. custom block placement) only by dividing total nodes among two categories like: homogeneous vs. heterogeneous or high performing nodes vs. low performing nodes. This policy helps to achieve better load rearrangement among the nodes and we can put data blocks actually where we want our data to be placed for the processing.
Optimization of the Optical Power Budget for Various WDM-PON Network Designs with Traffic Protection Securing

For the expansion of WDM-PON networks, it is necessary to have a detailed knowledge of the optical power budget in all its parts. This contribution shortly analyses various WDM-PON network designs with the traffic protection securing utilized only passive optical components in remote nodes. A main part is focused on the optimization of optical power budget possibilities for considered WDM-PON network designs. For evaluation of optical power budgets, a simulation model related to WDM-PON network designs and to interactions between various metropolitan and access parts in the optical distribution network is realized in the Matlab programming environment.
Inner Emotion Recognition Using Multi Bio-Signals

This paper proposes inner emotion recognition method using multi bio-signal which combines EEG (Electroencephalogram), EMG (Electromyography) and EOG (Electrooculogram) signals. EEG signal was used for recognizing inner emotion, EMG and EOG signals for removing artifact. The acquired data were processed and five emotions were classified using SVM(Support Vector Machine) in terms of arousal and valence, respectively. The experimental results show that the recognition rate of using multimodal bio-signals is 16.8% higher than that of using only EEG signal.
Data Hiding Scheme in Quad Channel Images using Square Block Algorithm

Steganography is a process of concealing the important information in a digital media which acts as a cover. A data concealing scheme in color images using both alpha and non-alpha channels is designed and implemented without decreasing the image quality and with minimal distortion. In the designed algorithm, data concealing in images is done using square block algorithm. The secret digits which are obtained in the implementation part of the algorithm are concealed in the cover pixel pairs with the help of reference matrix. Various security measures are calculated and the obtained results are found to be quite promising.
Probabilistic Load Margin Analysis Considering Stochastic Wind Power Fluctuations

In this paper, probabilistic load margin analysis has been investigated under stochastic wind power fluctuations. First, a distributed bi-directional sweep method is examined for power flow computations when wind power generators are connected to a power grid. Both fixed-speed and doubly-fed induction generators are considered. Secondly, a novel direct method is proposed to estimate the load margin. In the proposed approach, a bordered system is applied to investigate an iterative method in order to reduce computational complexities. Moreover, the proposed novel direct method can be integrated to the bidirectional sweep method such that the distributed load margin prediction can be achieved. Finally, the probabilistic load margin analysis can be performed by integrating the load margin sensitivity, based on the distributed load margin estimation, and Gram-Charlier expansion method. Numerical demonstrations on several IEEE systems have demonstrated the effectiveness of the proposed method.