Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear Series-Fed Patch Array with Dual Circular Polarization or Arbitrary Linear Polarization

A linear series-fed dual-port patch array working at 10 GHz with dual circular polarization or arbitrary linear polarization is proposed. This array consists of five circular patch elements which are serially excited by a traveling wave guided in a microstrip line. Despite that only five radiation elements are used, the array still exhibits high antenna efficiency greater than 93% averaged over the operation band. The typical trade-off between number of elements and antenna efficiency in series-fed array designs is overcome through the enhancement of coupling strength between the element and the feed line. The resulting high isolation between the two ports enables dual feeding configuration with low coupling. When only one port is excited, either right-handed or left-handed circular polarization radiation can be generated, as the sense of polarization is dependent on the traveling wave direction. When two ports are used simultaneously, arbitrary linear polarization can be realized by properly offsetting their phase difference. Based on reciprocity, this array can be also used for polarimetry applications. Experimental characterization on a fabricated antenna prototype validates the design.
Asymmetric Fault Propagation Mechanism on AC Side of Hybrid Microgrid And Suppression Methods

The analysis of asymmetric fault propagation mechanism on AC side and the study of its suppression methods are very important for the safe and stable operation of AC/DC hybrid microgrid. In this paper, the influence of asymmetric short-circuit fault on DC power and electricity is analyzed. On this basis, a compensation control strategy of negative sequence zero-sequence voltage is proposed to suppress the transmission of this type of fault. Then a hybrid micro-grid model using the control strategy of "network-network" interconnected converter is built on the simulation software PSCAD/EMTDC, which verifies the correctness of the above fault analysis and the effectiveness of the improved control strategy.1
Review and Applications of Virtual Synchronous Machines Technologies

Renewable energy such as solar or wind energy provides new possibilities to meet the world’s energy needs. However, connecting renewable energy sources to the power grid at a large scale will cause huge stability challenges at the connection interface. Virtual synchronous machine (VSM) technologies, which emulate the transient electromechanical characteristics of traditional synchronous machines, offer a unified interface for smart grid integration. With these technologies, all the renewable energy generators as well as the flexible loads could take part in regulating the grid frequency and voltage, thus improving the power grid’s stability. This paper presents the origin and development of VSM technology, and evaluates the mathematical model, control strategies and stability issues of the technology. It then summarizes VSM applications related to the grid interconnection of renewable energy, voltage sourced converter based HVDC (VSC-HVDC), motor speed regulation, and fast-charging interfaces. Finally, future research directions are assessed.
A Smart Classroom of Wireless Sensor Networks for Students Time Attendance System

Today, Wireless Sensor Networks (WSNs) have been included in many researches to form smart environments. IoT is becoming increasingly integrated in our daily life at homes, streets, schools and everywhere. Using IoT based on WSNs in the educational filed is an important resource for better preparing students for the future digital world. Digital students attendance system in schools or universities is an example for case that technology can facilitate the traditional ways for checking students attendance instead of using the manual paper sheets which consume time and resources with higher probability of failure. In literature, there are many time attendance systems that proposed to enhance the manual traditional methods for taking and calculating students attendance in smart ways. In this paper, we proposed a user friendly students time attendance system that can be applicable in different schools or universities in order to form a smart classroom based on WSNs and IoT technologies. We proposed intelligent chairs that can be identified as the sources of information, which integrated with four 50 kg load sensors and HX711 amplifier that measure the students weights and send the digital signals to a receiver in order to recognize the student presence during class schedule. This smart classroom is also installed with one ZKTeco ZK4500 fingerprint reader in order to increase the identification for students. The transmitted signals from the intelligent chairs will be connected by Android application which will be installed on the lecturers’ smart phones. So, teachers will get details and summary report of students attendance through the Android app. We implemented our proposed idea using java language, database and android system.
Study of Smart Condition Monitoring using Deep Neural Networks with Dropouts and Cross-Validation

The main focus of this paper to develop and analyse computational intelligence algorithm for smart condition monitoring. Smart condition monitoring is important and helps to solve some of the difficulties faced in terms of maintaining types of mechanical or electrical machines. This paper focuses on the ability to predict if a particular machine is in working condition or not based on a dataset provided. The dataset would consist of the actual data output that the smart condition algorithm can predict, and that there would be an accuracy based on the number of correct predictions. The implementation of the proposed work will be based on using deep neural network (DNN) with programming software Python. The algorithm will be trained on some of the parameters, while the remaining would be used for the testing process.
Filtering Techniques for Noise Reduction in Liver Ultrasound Images

Ultrasound is an important diagnostic tool in diagnosing various abnormalities in the liver. Ultrasound is safe strategy for patient examination, being easy to apply, a non-invasive, and economical one. Ultrasound examination has the probability of repeatability producing images in real-time mode for diagnosing abdominal disorder such as liver cancer. Unprocessed ultrasound image has poor quality due to loss of texture or shape that can affect expert interpretation. The filtering methods are the initial process to reduce noise in the images. Enhanced image quality is needed for processing at the next stage after this initial processing. The research used salt and pepper, gaussian, and speckle noise. Filter that used to improved image quality to reduce noise are; mean, 2D medians, 3D medians, gaussian, and wiener. Image quality is measured by the quantitative value of MSE, RMSE and PSNR. Filter testing is done with noise level 1 and each filter has sigma value with average of 5. From the trial results, the best method for handling salt and pepper noise is the 3D median filter with MSE and RMSE values approaching 0 then having PSNR greater than 30 dB of all filter. The wiener filter is the best method to overcome Gaussian and speckle noise.
A phase II trial of the mTOR inhibitor AP23573 as a single agent in advanced endometrial cancer

5516 Background: There are few effective therapies for women with advanced or recurrent endometrial cancer. Targeted therapies such as AP23573, a novel mTOR inhibitor, may result in clinical benefit with fewer side effects. Preliminary results of a trial of single agent AP23573 in patients with progressive endometrial cancer who may have had up to 2 prior regimens of cytotoxic chemotherapy are reported. Methods: The trial is an open-label, Simon 2-stage, single-arm study enrolling patients who have advanced endometrial cancer with documented progression in the 3 months prior to entry. Patients receive 12.5mg AP23573 QDx5 as a 30-min. intravenous infusion every other week for 28-day cycles. The primary efficacy endpoint is Clinical Benefit Response (CBR), defined as a complete or partial response or prolonged stable disease (= 16 weeks) by modified RECIST guidelines. Results: Seven of the first 19 patients achieved CBR, allowing expansion to the second stage. Enrollment is now complete (45 patients). Demog.
Computer Modeling of Temperature Dependent Resistance of Carbon Nanotubes Interconnects

In this paper the temperature dependent resistance of carbon-based interconnects is described using parameterized SPICE computer model. The obtained resistance values are then used for carbon nanotube (CNT) a thermally aware model considering the temperature coefficient of resistance (TCR). The models have been created for both SWCNT and MWCNT. Parameterized computer SPICE models of higher accuracy for SWCNT bundle and MWCNT interconnects are proposed. Verification has been made to confirm the applicability of the advanced computer models.
Gait Analysis Using Smartwatches

Monitoring gait characteristics is an important tool used in many areas including orthopedics, sports, rehabilitation and neurology. Current methods applied to analyze the gait need clinical settings and equipments for measuring gait parameters. In this study, we propose an unobtrusive and comfortable system to perform gait analysis using smartwatches. Accelerometer and gyroscope sensors of the smartwatch are used to extract three main parameters of gait: step length, swing time and stance time. This study is one of the first smartwatch based gait analysis studies focusing on extracting these spatio-temporal gait parameters. Data is collected from 26 healthy participants in clinical settings. The data is preprocessed and step features are extracted. Gait parameters are estimated using various regression models and compared with the ground truth data coming from the clinician using the golden standard instrumented walkway.
Real Time Multi-lane Detection Using Relevant Lines Based on Line Labeling Method

We propose a real time multi-lane detection algorithm using monocular camera mounted in front of the vehicle. The proposed algorithm is focused on reducing computation time by using line labeling method. Through the line labeling method, the algorithms requiring high computation time such as RANSAC and vanishing point estimation are able to process efficiently. The proposed algorithm is evaluated on both our dataset and Caltech Lane Dataset. The experimental results show that the computation time of the proposed algorithm takes 18.7ms per frame in our dataset which is suitable for real time application and achieving comparable accuracy to previous study.
Look-Ahead Strategic Offering for a Virtual Power Plant: A Multi-Stage Stochastic Programming Approach

The increasing number of distributed energy resources on the distribution side has promoted the development of virtual power plants to become active market participants. Considering the uncertainty in the market price and the wind generation in a virtual power plant (VPP) in the real-time operation, this paper proposes a look-ahead real-time offering strategy using a multistage stochastic programming formulation within each look-ahead horizon. We test the proposed model on a small virtual power plant. The supply offer curve and the demand offer curve for different market price cases are determined, and the operating states for the VPP system and its components under different scenarios are also obtained. Using the proposed look-ahead approach, the VPP can determine the rolling offer curves continuously to participate in the real-time electricity market.
Performance of MLACA with Modified Grouping for Superconducting Circuit Analysis

Inductance extraction for superconducting integrated circuits requires knowledge of the structural current distribution. FastHenry is a well-known magnetoquasistatic analysis tool for solving the current distribution. FastHenry is based upon the partial element equivalent circuit (PEEC), volume integral equation method. It is a method of moments (MoM) formulation. FastHenry employs the multilevel fast multipole algorithm (MLFMA) for compressed storage of the mutual inductance matrix. Recently, a multilevel adaptive cross approximation solver with singular value decomposition recompression (MLACA-SVD), and with modified grouping strategies for increased efficiency, has been proposed as an alternative fast solver within FastHenry. This paper presents further results with MLACA-SVD and group merging, for a volumetric superconducting structure, such that unknowns are distributed roughly evenly throughout a cubic domain. This is in contrast to the predominantly planar structures considered before. The results show that the group merging schemes are broadly applicable to general volumetric structures, for increased efficiency. The results could be relevant to other applications of FastHenry and of ACA.
Systematic Design of an Ultra-Wideband Six-Port Multi-Mode Antenna Element Using Symmetry Properties of Characteristic Modes

A design of an ultra-wideband six-port multi-mode antenna element intended for use in a massive MIMO array is presented. By leveraging symmetry properties of characteristic modes, six uncorrelated antenna ports can be defined on a square plate while offering wideband potential with minimum dimensions. Excitation slots are introduced and systematically optimized based on symmetry considerations in such a way that an inherent impedance match is realized for all six ports. In order to cover the desired ultra-wide bandwidth from 6 GHz to 8.5 GHz, the excitation slots are stepped in width and the feed network is adjusted accordingly, achieving the design goals.
Additive Manufactured Bandpass Filters at Ka-band

This paper describes the development of an additive manufactured waveguide filter operating at Ka-band for satellite applications. The filter is designed to allow the build in a specific orientation to allow possible further integration with other components. The manufacturing process allows the parts to be realised monolithically. Measured performance of the filters is presented and compared to simulations.
Analysis of Voltage Stability Weak Nodes Location and Optimization Measures in DC Multi-infeed Receiving-end Power Grid

With the nationwide deployment of renewable energy power DC multi-infeed receiving-end system forms at the load center. The AC and DC system interaction increases the effects to power system security and stability. The AC system fault may lead to DC system commutation failure or even DC block. Voltage collapse may be caused by a large-scale power flow transferring subsequently. A comprehensive application method of continuation power flow, serious contingency screening and modal analysis is proposed to find static voltage stability limit and locate weak nodes. Southern Jiangsu power grid is studied to verify it. A reactive power compensation measure for voltage stability optimization installing FACTS device at weak area is given, which can improve the voltage stability limit and voltage recovery level of DC multi-infeed receiving-end power grid.
Uncertainty propagation in phaseless electric properties tomography

Uncertainty propagation in a phaseless magnetic resonance-based electric properties tomography technique is investigated using the Monte Carlo method. The studied inverse method, which recovers the electric properties distribution at radiofrequency inside a scatterer irradiated by the coils of a magnetic resonance imaging scanner, is based on the contrast source inversion technique adapted to process phaseless input data.
Analysis of Skin Marks Through the Use of Intelligent Things

Melanoma is one of the more frequently encountered cancers, which quite often depends on exposure to ultraviolet radiation occurring in solar radiation. Of course, an additional factor is individual immunity and genetics. It is important to discover the possible spread of the cancer, which in this case depends on the observation of the skin, and above all the marks. The quickest possible detection of neoplastic changes can result in a chance to prolong life. In the era of mobility, where everyone has a camera built into the phone and access to the Internet, it is possible to analyze signs by an application that would analyze the skin. In the case of detected exceptions, the application would exchange information with a publicly available database and consult with a dermatologist about the possible need for urgent hispatological examination. In this paper, we propose a model of such a system based on intelligent things along with a detailed description of individual components. As a classification component, a convolutional classifier was proposed, which accepts not only image data, but also numerical one. The analysis of the proposed solution has been tested and discussed due to numerous advantages and disadvantages of such a solution nowadays.
Waveform Design for Simultaneous Wireless Information and Power Transfer

A good alternative to extend the lifetime of wireless devices placed in remote locations is to be able to obtain energy through a technique generally called Simultaneous Wireless Information and Power Transfer (SWIPT). Furthermore, since relays are commonly used to expand the coverage of wireless systems, an interesting choice could be they also harvest energy for its operation. It is shown in this work that, taking advantage of known modulation formats and having available the Channel State information (CSI), it is possible to make the power transmission more efficient. Using a SWIPT scheme known as Time Switching (TS), a study is carried out to highlight novel improvements in energy efficiency and outage probability.
A Rigorous Orbit Attitude Estimation Algorithm for Low-Earth-Orbit Spacecrafts

In this paper, a rigorous orbit attitude estimation algorithm for low-Earth-orbit (LEO) spacecrafts is presented in the presence of earth oblateness and atmospheric drag. The spacecraft orbit attitude kinematics for arbitrary eccentric orbit is derived. The variational orbit angular velocity is computed using the inertial position and velocity. The effects of the orbit estimation precision with respect to orbit attitude determination are analyzed. An extended Kalman filter (EKF) is derived to estimate the orbit attitude, inertial position and velocity, as well as gyro bias. Simulation results indicate that the proposed algorithm has better estimation performance for the orbit attitude over than the traditional algorithm.
New Technique of Social Aware Routing Protocols in Delay Tolerant Network

Delay Tolerant Network (DTN) is a challenge network that can tolerate long delays during connections. It is different from traditional networks because traditional networks cannot meet the needs of disrupted and challenged networks. In this article, we will discuss the delay-tolerant network bundling protocol, which is located between the application layer and the transport layer. It is used as a communication system to meet the needs of the Internet. Delay Tolerant Network (DTN) has a coordinated, long-term and profitable surplus. Therefore, most systems use the “Transfer by Key” policy for data transfer, but the main problem with this strategy is to choose the best queue and the best commit time. Therefore, in order to solve these problems, social systems are used to delay the network. After a detailed discussion of social relationship, three routing strategies were proposed based on location, conference-based routing, and community-based approaches. We have chosen a routing strategy for three of these protocols to compare socially sensitive, ie popular routing protocols, routing protocols and spray waiting for prophets and routing protocols. These protocols are compared using a simulator based on discount rate, average latency, overload rate and hop count used. After comparison, we conclude that the spray and hold routing protocol is based on the best choice of transfer rate, overload rate and hop count.
Health Programme Evaluation by Propensity Score Matching: Accounting for Treatment Intensity and Health Externalities with an Application to Brazil

Most of the literature on health programme evaluation has estimated average programme impacts relying on either: (i) data on the presence or absence of an intervention in a particular locality, or (ii) data on individual participation in the health programme. By estimating an average health impact which is independent of the programme's population coverage, the empirical approaches of these studies overlook the important fact that public health interventions create externalities whose magnitude depends crucially on the number of covered individuals in a locality. The lain contributions of this paper are to suggest and apply an empirical approach for the impact evaluation of public health interventions which also takes into account treatment externalities, when non-experimental, routine data are available and under the assumption of average treatment effects by a propensity score matching-difference-in-differences estimator adapted to the case of multiple treatments, jointly evaluating the impact of different programme coverage levels. The methods are used to conduct an impact evaluation of the Family Health Programme (Programa Saude da Familia - PSF), the broadest health programme ever launched in Brazil, on adult and child health.
Wireless Power Transfer to Intra-Abdominal Implants Using an Around-the-Body Loop Antenna

We study the wireless powering of intra-abdominal implants using a wearable around-the-body loop antenna. The study includes the wireless link characterization and modelling of the specific absorption rate (SAR) obtained by an anatomical human body model and a simplified homogenous elliptic cylinder model. We also assess the robustness of the system in terms of the power gain uniformity at the cross-sectional plane of the abdominal cavity. Overall, our system achieves the link power efficiency of −6.6 dB at 7.25 MHz to an implant (2.3-by-2.3 cm square loop) at the center of the abdominal cavity. According to SAR analysis, under the 1.6 W/kg limit, we can transmit 530 mW and the maximum power available at the implant is 149 mW with the voltage amplitude of 3.6 V. Moreover, the voltage at the implant remains above 1 V for transmission power levels down to 10% of the maximum.
Recommending Web Service by Predicting Quality of Service using Hidden Markov Model

Owing to rapid growth of web services in service-based systems, the user should be provided with efficient service quality evaluation methods. Service quality is one of the most important features of software quality to predict the overall performance that helps to decide which web service should be manipulated. Both reliable and unreliable users are contributed by the service quality values leads to inaccuracy of the forecasting outcomes. To overcome this problem, we proposed the approach to detect the forecasting results accurately in unknown web service quality values using Matrix Factorization by Reputation with Hidden Markov Model (HMM). The experimental outcome shows that our proposed approach has improved accuracy to predict the reliable and unreliable users with other existing approaches.
Smart Resistor: Stabilization of DC Microgrids Containing Constant Power Loads Using High-Bandwidth Power Converters and Energy Storage

Power electronic converters and electric motor drives have found increased application in dc microgrids, electric automobiles, and ships. Such converters when driving loads in a regulated fashion act as constant power loads (CPLs). These CPLs can cause destabilizing effects on the grid because of their negative incremental impedance. This paper proposes a method to dynamically stabilize CPLs at the point of load by making them behave as adaptive Smart Resistors by using high-bandwidth power converters and energy storage units. These Smart Resistors can work with smart sources to realize ultimate intelligent power networks. The control strategies needed to achieve the concept, including voltage and current trajectory control principles, are analyzed and validated with a hardware test setup.