Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Transitively Closed Undirected Graph Authentication Scheme for Blockchain-Based Identity Management Systems

Blockchain can potentially be deployed in a wide range of applications due to its capability to ensure decentralization, transparency, and immutability. In this paper, we design a cryptographic membership authentication scheme (i.e., authenticating graph data) to support blockchain-based identity management systems (BIMS). Such a system is designed to bind a digital identity object to its real-world entity. Specifically, we introduce a new transitively closed undirected graph authentication (TCUGA) scheme, which only needs to use node signatures (e.g., certificates for identifying nodes). The trapdoor hash function used in our scheme allows the signer to efficiently update the certificates without the need to re-sign the nodes. In other words, our scheme is efficient even though the graph dynamically adds or deletes vertices and edges. Moreover, our proposal can efficiently provide a proof when the edge between two vertices does not exist, thus solving the existing intractability issue in transitive signature (the main tool for authenticating graph data). Finally, we prove the security of our proposed TCUGA in the standard model and evaluate its performance to show its feasibility for BIMS.
Collaborative collision detection with half-duplex radios

We present and analyze CSMA/CDS, a simple extension of carrier-sense multiple access (CSMA) that attains collision detection (CD) through the collaboration among nodes endowed with half-duplex radios in wireless local area networks (WLAN). CSMA/CDS uses two mechanisms to provide feedback to nodes attempting to transmit data packets concurrently. Using carrier sensing to access the channel, a node transmits a common pilot before sending its data packet, and a designated passive listener sends a collision pilot if it does not hear the common pilot after detecting carrier. This ensures that no collisions of data packets can occur. The throughput of CSMA/CDS is analyzed and compared with the performance of CSMA with priority ACKs and CSMA with collision detection (CSMA/CD), which assumes full-duplex transceivers. The results show that the throughput of CSMA/CDS is much better than the throughput of CSMA and is comparable to that of CSMA/CD.
Robust state feedback current controller with harmonic compensation for single stage grid connected PV inverter with LCL filter

The paper presents the robust state feedback output current controller for single stage grid connected photovoltaic array (PV) inverter interfaced to grid through LCL filter. The robust state feedback current controller is based on mixed H2/H with regional pole placement constraints approach. The controller enhances the system performance and robustness to grid disturbances as well as also enhances the power quality with the help of robust harmonic compensator utilizing resonant controller tuned for fundamental, 5th and 7th harmonics. It also mitigates the need of passive damping for LCL resonance. The state feedback current control is formulated in stationary reference frame and obtained by solving linear matrix inequalities (LMI). Simulation results tests the controller performance under different solar irradiance and linear load conditions as well as grid voltage disturbances.
The Great Fantasy Migration : Exploring Individual Differences in the Move to an Online World

Individuals in the United States spend increasingly more time online and in virtual worlds, averaging 20.5 hours per week (Ofcom, 2015). I test a potential explanatory model for this shift, the Great Fantasy Migration hypothesis (GFM). The GFM proposes that the move to a virtual or fantasy realm is driven by a combination of high levels on narcissism and low levels of trust or confidence in the world. Virtual or fantasy realms allows esteem needs to be met without the level of challenge that it takes to meet these needs in the “real” world. In Study 1 (N=300) I tested participants’ levels of grandiose narcissism, pessimism, geek culture engagement, and time on social media. Study 2 (N=600) served as a preregistered replication of Study 1 with the addition of items testing the effects of gender and positive emotionality. Both studies supported the GFM.
Energy-efficient mission planning of UAVs for 5G coverage in rural zones

We target the problem of providing 5G network connectivity in rural zones by means of Base Stations (BSs) carried by Unmanned Aerial Vehicles (UAVs). Our goal is to schedule the UAVs missions to: i) limit the amount of energy consumed by each UAV, ii) ensure the coverage of selected zones over the territory, ii) decide where and when each UAV has to be recharged in a ground site, iii) deal with the amount of energy provided by Solar Panels (SPs) and batteries installed in each ground site. We then formulate the RURALPLAN optimization problem, a variant of the unsplittable multicommodity flow problem defined on a multiperiod graph. After detailing the objective function and the constraints, we solve RURALPLAN in a realistic scenario. Results show that RURALPLAN is able to outperform a solution ensuring coverage but not considering the energy management of the UAVs.
Voltage & frequency stabilisation of a SEIG based micro-hydro system through a DFIG based WECS equipped with BESS

In this paper an improvised micro-grid system is considered which is capable of delivering power to the local time varying loads. The system taken in this work consists of multiple sources i.e. a constant power micro-hydro system, a WECS along with a BESS. The constant power micro-hydro houses a 22KW SEIG which delivers power to the local loads. At the dc link of the WECS a BESS has been connected. GSC of the WECS acts like a STATCOM. During various loading conditions, the Active and Reactive power produced by the SEIG is not sufficient; therefore there is a mere fluctuation in systems voltage and frequency. Therefore GSC delivers the required power to the system, maintains the frequency and voltage to be constant and improves power quality in the system. The Grid Side Converter also manages the active power of the system by storing the excess power in the BESS and supplying it when needed in the night time. Various types of loads such as linear RL load, Non-Linear load, and Dynamic load are taken into account to evaluate the performance of the hybrid micro grid system. The above simulation is done using MATALB/Simulink environment.
Convolutional neural network application for cells segmentation in immunocytochemical study

HER2/neu status of breast cancer is important for treatment strategy choice, but nowadays it is evaluated manually by pathologist. The automation of this procedure is an urgent task, because it will allow to free a pathologist from routine work. But the problem of cells segmentation is difficult for classical methods of computer vision due to the frequent presence of erythrocytic background and non-cellular elements at specimen' image. In this work we propose segmentation algorithm, based on deep convolutional neural networks. Is it has been shown that using this approach, it's possible to get better results, than using classical computer vision algorithms.
Outage Probability Analysis and Dynamic Criterion Calculation Under the Plasma Sheath Channel

Dynamic plasma sheath can lead to the communication interruption because of its severe impact on the electromagnetic waves. Existing studies mainly focused on the numerical analysis, either regarding the specific experimental results or regarding the computational modeling of the plasma sheath channel, without theoretical and quantitative analysis of the communication performance. In this paper, the bit error rate and the outage probability with $m$ -ary frequency shift keying modulation are derived theoretically based on the hidden Markov model of plasma sheath channels. Specifically, since the outage probability can be viewed as the probability of an interruption in the communication system, it can reflect the intensity of the channel dynamics. Therefore, we analyze the effect of channel model parameters on the outage probability and propose a dynamic criterion calculation formula to model the dynamic of the plasma sheath channel. Finally, simulation results are carried out to reveal a positive correlation between the dynamic criterion and the outage probability, which shows that the dynamic criterion calculation formula can accurately illustrate the dynamic of the plasma sheath channel and the communication performance.
Army artillery munition warhead explosive fill probabilistic risk analysis

Military grade energetics are, by design, required to operate under extreme conditions. As such, warheads in a munition must demonstrate a high level of structural integrity in order to ensure safe and reliable operation by the Warfighter. In this example which involved an artillery munition, a systematic analytics-driven approach was executed which synthesized physical test data results with probabilistic analysis, non-destructive evaluation, modeling and simulation, and comprehensive risk analysis tools in order to determine the probability of a catastrophic event. Once the severity, probability of detection, occurrence, were synthesized, a model was built to determine the risk of a catastrophic event during firing which then accounts for defect growth occurring as a result of rough-handling. This comprehensive analysis provided a defensible, credible, and dynamic snapshot of risk while allowing for a transparent assessment of contribution to risk of the various inputs through sensitivity analyses. This paper will illustrate intersection of product safety, reliability, systems-safety policy, and analytics, and highlight the impact of a holistic multidisciplinary approach. The benefits of this rigorous assessment included quantifying risk to the user, supporting effective decision-making, improving resultant safety and reliability of the munition, and supporting triage and prioritization of future Non-Destructive Evaluation (NDE) screening efforts by identifying at-risk subpopulations.
PBPK Modeling Strategy for Predicting Complex Drug Interactions of Letermovir as a Perpetrator in Support of Product Labeling

Letermovir is a human cytomegalovirus (CMV) terminase inhibitor for the prophylaxis of CMV infection in allogeneic hematopoietic stem‐cell transplant (HSCT) recipients. In vitro, letermovir is a time‐dependent inhibitor and an inducer of cytochrome P450 (CYP)3A, and an inhibitor of CYP2C8 and organic anion transporting polypeptide (OATP)1B. A stepwise approach was taken to qualify the interaction model of an existing letermovir physiologically based pharmacokinetic model to predict letermovir interactions with CYP3A and OATP1B. The model was then used to prospectively predict the interaction between letermovir and CYP2C8 substrates such as repaglinide, a substrate of CYP2C8, CYP3A, and OATP1B. The results showed that letermovir modestly increased the exposure of CYP2C8 substrates. These results were used to inform the US prescribing information in the absence of clinical drug–drug interaction studies. In addition, midazolam interactions with letermovir at therapeutic doses were also simulated to confirm that letermovir is a moderate CYP3A inhibitor.
Robust Missile Autopilot Design Using Two Time-Scale Separation

In this paper, time-scale separation, feedback linearization (FL), and extended state observer (ESO) based new design for an acceleration tracking pitch autopilot of a tail controlled, skid-to-turn tactical missile is presented. The pitch plane dynamics has been split into pitch rate dynamics as fast, and the acceleration dynamics as a slow subsystem by exploiting the naturally existing time-scale separation between them. FL-based controllers are then designed for the subsystems separately. To achieve robustness in the presence of uncertainties and disturbances, an ESO is designed for each of the subsystem separately. The ESOs estimate the effect of uncertainties in the respective subsystem and the estimate is used to robustify the feedback linearizing controller designed for the respective nominal subsystem. The design neither requires accurate plant model nor any information about the uncertainty. Closed-loop stability for the overall system is established. The effectiveness of the design in meeting specified tracking performance in the presence of significant uncertainties, unmodeled dynamics, measurement noise, control input, and rate saturation, and in varying missile velocity and altitude scenario is illustrated by simulation. Furthermore, to analyze the performance for different initial conditions and parameter perturbations, Monte Carlo simulation study is carried out and the results are presented. Finally, performance comparison of the proposed design with some existing controllers is presented to showcase the efficacy of the proposed design.
Short length non-binary rate-adaptive LDPC codes for Slepian-Wolf source coding

In this paper, we consider the construction of a Slepian-Wolf source coding scheme in a context where only a small amount of data has to be transmitted to the decoder. In this context, we propose a novel rate-adaptive Slepian-Wolf code construction that is based on non-binary LDPC codes. The construction we propose replaces the regular accumulator of the standard LDPCA method by a local graph that is optimized at every rate of interest. In our method, the local graph is specifically designed in order to give good decoding performance at short length, while existing LDPCA constructions are usually optimized under an infinite codeword length assumption. Our simulation results on short codes obtained from our design method show a FER improvement of up to an order to magnitude compared to the standard LDPCA construction.
Visual Pattern Recognition Using Enhanced Visual Features and PSD-Based Learning Rule

This paper proposes a feedforward visual pattern recognition model based on a spiking neural network (SNN). The proposed model mainly includes four functional layers: 1) feature extraction; 2) encoding; 3) learning; and 4) readout. A modified HMAX model is first presented to extract features from external stimuli. In order to reduce the computational cost, we simplify the S1 layer using a single Gabor filter window. To simulate biological vision’s sensitivity to the vertical direction, we strengthen the feature of filtered orientation in 90° by adding a sharpened replica of the filtered image in 90° before max pooling in C1 layer. Then the phase encoding approach is used to convert the extracted visual features into spike patterns. These spike patterns will be learned by precise-spike-driven-based learning rules in an SNN. Finally, experimental results on benchmark datasets including MNIST, Caltech 101, and optical characters demonstrate the efficiency and robustness in noisy environments of the proposed model.
A Limb-Based Graphical Model for Human Pose Estimation

Modeling the relationship among human joints is one of the most important components in human pose estimation. Most of previous methods define this relationship as a geometric constraint on the relative locations of two neighboring joints. In this constraint, the local appearance of the region connecting two neighboring joints is ignored. However, discarding this image appearance leads to some severe problems, such as double-counting and localization failure when the human pose is rare in the training dataset. Moreover, this image appearance, called human limb, plays an important role in human pose estimation in human visual system. Due to these reasons, we propose to solve a new task: human limb detection, which aims at detecting and representing this local image appearance. We combine this task with human joint localization as a unified framework. After getting the initial detections, we design a two-steps graphical model to capture the spatial relationship among human joints and limbs in a coarse to fine way. We evaluate the proposed method on two widely used datasets for human pose estimation: 1) frame labeled in cinema and 2) leeds sports pose datasets. The experiments results show the effectiveness of our method.
Compact triple-band circularly-polarized directional antenna for UHF/ISM RFID mobile readers with GNSS band

Multi-band, multi-function, and miniaturization are very desirable for late-mode wireless mobile devices. In this paper, a compact triple-band circularly-polarized directional antenna at 920MHz, 1600MHz, and 2450 MHz is proposed for UHF/ISM RFID mobile readers with GNSS band. The antenna consists of a two-feed network and stacked radiating patches. Measured result shows that the 10 dB impedance bandwidths are 24, 430, and 340 MHz with 3-dB axial ratio bandwidths of 13, 230, and 365 MHz for the three bands. In these bands, the antenna provides the symmetric radiation patterns and the peak gains of 3.7, 6.6, and 8.8 dBic, respectively. Comparison shows that the antenna not only features compact size, simple configuration, and low cost but also provides wide CP bandwidths. Moreover, the operating frequencies can be changed conveniently and the large frequency ratio of 2.8 is achieved. It is the first design to integrate the UHF/ISM RFID reader application and GNSS function into a single antenna.
An overview on the deep learning based prognostic

The systems of prognostic and health management (PHM) aim to locate all kinds of anticipated faults by determining the remaining useful life of a certain system. Existing traditional methods try to find a solution to the problem of detecting faults and predict the future behavior of the machine. However, these methods suffer from some limits such as features extraction manually. To bypass those limits, Deep Learning has the ability to analyse and process large data using helpful techniques. This paper presents the utility of Deep Learning in prognostics. In addition, the present paper displays the difference between the mention methods with the existing ones through a comparison.
PV-battery based single phase microgrid with grid synchronization and de-synchronization capabilities

In this paper presents an integration of battery with a PV grid tied based single phase microgrid with multifaceted facilities. The proposed PV-battery grid tied system has capability to perform in dual mode i.e. grid integrated mode and islanded mode, according to the availability of grid. The proposed system has multipurpose control for VSC (Voltage Source Converter), for power transfer, harmonic elimination and provides power balance to the microgrid. The purpose of this system is to supply uninterrupted power to the load at less PV generation or grid fault condition or at peak load condition by using a battery. This system is modeled in MATLAB and developed model is used to simulate its performance. Simulation results are analyzed the performance and the response of microgrid with an adaptive algorithm with frequency and voltage control under mode transition condition.
Relay based wireless networks with joint modulation, power allocation and relay selection

In this paper we consider performance improvement of decode and forward (DF) relays via joint modulation at relays, power allocation across the relay nodes and relay selection. Initially, we consider a canonical relay network scenario consisting of three nodes, of which two of them constitute source and sink nodes and one of them would act as a relay. The source and sink nodes cannot reach each other directly and therefore rely on the relay for data forwarding. We assume all the three nodes use orthogonal frequency division multiplexing (OFDM) as the physical (PHY) layer transmission mechanism. Further it is assumed that, the relay node performs joint modulation on the data received from both the nodes as described in [1] (henceforth referred to as decode and forward joint modulation (DFJM)), thus creating a broadcast frame which is then transmitted to both the nodes. The performance of this DFJM at relay is compared against the simple DF technique in which relay does not perform any processing. Our simulation results suggest that the former outperforms the latter in terms of throughput. Our simulation results also suggest that the throughput improvement with DFJM against the simple DF technique was found to be much higher in networks that are asymmetric with respect to transmission rates. Next we consider the performance of DFJM scheme with relay selection and power allocation by considering a relay based network with more than one relay in it. Our simulation results on this aspect suggest that an equal power allocation among various relays gives better throughput values as against that of the scheme where relay selection is combined with optimal power allocation. This behavior is contrary to what was observed in a related work where simple analog relays were considered [2]. The relatively better performance of the DFJM scheme with equal power allocation as against that of the scheme with relay selection followed by optimal power allocation can be attributed largely to the following: (i) less number of transmission slots that a DFJM based scheme would require and (ii) the inherent diversity advantage of having all the relays transmit.
Single phase symmetrical and asymmetrical design of multilevel inverter topology with reduced number of switches

Multilevel Inverters have shaped a new trend of importance in industry and research. A new topology of multilevel inverter is proposed in this paper which can be operated in symmetrical and asymmetrical modes. The proposed topology produces 7-level and 13-level staircase output voltage waveform for symmetrical and asymmetrical configuration respectively using only 10 switches. The gate signals for the different switches are produced employing the fundamental frequency switching technique. The topology achieves better performance using a lower minimum number of components in comparison to conventional inverters. These improvements result in reduced system cost and size. Simulations are carried out using MATLAB/SIMULINK environment and experimental implementation using laboratory prototype module have ascertained the performance and operation of the proposed topology.
Adaptive Finite-Time Attitude Tracking Control for Spacecraft With Disturbances

In this paper, the adaptive finite-time attitude tracking control problem for rigid spacecraft with upper bounds unknown external disturbances is studied by using a novel combining control scheme of adaptive control technique and adding a power integrator (AAPI) technique. An adaptive finite-time control law with boundary layer is first established under the proposed combined control scheme, which can attenuate the influences of disturbances and contain the advantages of AAPI technique. Then, another adaptive finite-time control law without boundary layer is further given, which can simply the control design. It is proved that both the two control laws can ensure the tracking errors converge to the desired regions in finite-time. Moreover, since the established two control laws are both designed with continuous control architecture, the chattering problem is eliminated, which are more adopt to practical engineering applications. An example is included to show the effectiveness of the proposed methods.