Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Power Control Based on Lyapunov Optimization Framework for Decode-and-Forward Relay Systems With Energy Harvesting

This paper studies the power control in a two-hop decode-and-forward relay system over fading channel. The relay node is an energy harvesting node and is equipped with a data buffer and a rechargeable battery with finite capacity. Under the condition that any prior and statistical knowledge about the harvested energy and channel fading is unknown, based on the Lyapunov optimization framework, an online power control strategy for the source node and the relay node is proposed to maximize the average transmission rate and minimize the average energy consumption of the source node. First, the optimization problem is decomposed into two sub-problems: minimizing the average energy consumption of the source node and maximizing the average transmission rate of the relay node. Then, we use the Lyapunov optimization framework to transform the minimization and maximization problems to the minimization of the upper bounds of two “drift-plus-penalty”s and solve them. The solution of the optimization problem only relies on the current channel coefficient, the state of the data buffer, the energy level of the battery in the current time slot, and the average transmission rate of the past time slots. Only a few calculations are needed to get the optimal power of the source node and the relay node. Finally, simulation is done to verify the performance of the proposed algorithm. The simulation results show that the transmission rate difference between the proposed algorithm and the ideal offline water filling algorithm is small, which has full knowledge of energy and channels in advance and is without the constraints of the causality of energy and data, and the overflow of the battery and data buffer. The proposed algorithm is greatly superior to the online greedy algorithm and the semi-greedy algorithm.
CSR VS WOMEN : POTENTIAL APPLICANTS ’ EXPECTATIONS OF CSR AND GENDER DIFFERENCES

Companies are increasingly paying attention to corporate social responsibility (CSR) as they expect it to affect their attractiveness as employers. However, the question is whether prospective applicants expect social responsiveness from a future employer and how gender differences affect those expectations. The purpose of this study was to identify expectations that potential applicants have in terms of CSR from a prospective employer, and how gender differences affect applicants’ expectations. Using a sample of 153 business students, the study reveals that gender differences matter. The results demonstrate higher CSR expectations of a prospective employer among women. The results are statistically important for such CSR aspects as the fair employee evaluation process, support for additional education, full information to customers, contributions to charities and corporate environmental responsibility. Additionally, the findings state the ratio of women to men expecting a total CSR from a prospective employer with said ratio being 5:1. ARTICLE INFO Available online 3 September 2017
A Flexible Framework for Exploring, Evaluating, and Comparing SHA-2 Designs

Hash functions are a crucial tool in a large variety of applications, ranging from security protocols to cryptocurrencies down to the Internet-of-Things devices used, for example, as biomedical appliances. In particular, SHA-2 is today a ubiquitous hashing primitive. Its acceleration has driven a wealth of contributions in the technical literature and even a whole industry segment involving dedicated hash processing accelerators. Because of the variety of requirements in terms of performance, resources, and energy consumption as well as the impact of the particular hardware technology of choice, evaluating and comparing different architectural schemes is a nontrivial task, along with the exploration of new solutions matching given user requirements. Based on a careful review of the state of the art, this paper introduces an SHA-2 workbench to be used as a framework for evaluating different implementation styles and architectural choices. The workbench comes in the form of a generic HDL description, where the various implementation options are exposed in the form of user-configurable parameters and can be variously combined obtaining either known solutions or possibly new configurations to be explored. We systematically use the workbench to analyze the available SHA-2 architectural techniques. This extensive evaluation provides a deep understanding of the performance and energy implications of each implementation style and even allows the identification of nonobvious matches between architectural choices and target technologies in order to optimize hash rate and area efficiency figures.
Smart Coastline Environment Management Using Deep Detection of Manmade Pollution and Hazards

A significant portion of the tourism industry and the fishing communities depend on the health of the seashores for their livelihood. Visual interpretation of this environment provides the required information for autonomous agents for decision support in large-scale operations such as smart beach management. Deep Neural Networks (DNN) are recently used for image classification and scene understanding with very good results. In this paper, a DNN is used for object detection in the scenes from seashore areas. This interpretation is used for decision support for various smart beach applications. The technique used for smart beach scene interpretation is the transfer learning on a pre-trained DNN using VGG architecture. The Single Shot Detector (SSD) technique is used for object detection in the collected dataset from the beach areas. A dataset from the beaches of the Caspian Sea is collected in order to provide an extensive simulation in the real-world setting. The experimental results showed that the accuracy of the presented technique is acceptable for various applications in the seashore environment.
Identifying Vehicle’s Steer Change via Commercial Smartphones

This paper focuses on the problem of sensing vehicle’s steer change via smartphones. Different from other works, we propose a framework that only use off-the-shelf smartphone’s IMU sensors to detect and classify the vechicle’s steer change during driving. First, we achieve a sensor fusion method based on Kalman Filter to get smartphone’s attitude accurately in order to get the relationship between smartphone coordinate and vehicle coordinate. Step further, in the process of steer change classification, we propose a multi feature score method to classify lane change pattern and use K-means algorithm to differentiate left turn, right turn and U-turn pattern. From the experiment results in real driving condition, the classification accuracy is acceptable at around 90% in average.
Classification of Glycyrrhiza Seeds by Near Infrared Hyperspectral Imaging Technology

The near infrared hyperspectral imaging technology was used to classify glycyrrhiza seeds, which laid a theoretical foundation for the development of the equipment for the selection of glycyrrhiza seeds. Having Taken 475 glycyrrhiza seeds from four different origins, three varieties and two planting patterns as samples, 288 bands of hyperspectral images were collected in batches in the range of 948–2512 nm. Full bands were used to establish the PLS-DA discriminant model. The SVM discriminant model based on characteristic bands was established by PCA. Experiments showed that the two discriminant models had their own merits in the three aspects of origins, varieties and planting patterns, and the SVM model accuracies of training set and test set were more than 93%. We can draw a conclusion from the experiments that near infrared hyperspectral imaging combined with model discriminant analysis could be used to identify the origins, varieties and planting patterns of glycyrrhiza seeds.
On the Variation of Optical Return Stroke Speed Along the Bottom of Lightning Channel

In cloud-to-ground lightning flash, a varying return stroke speed during the propagation process along the lightning channel has been extensively reported. It is also reported that as the return stroke propagates upward, the waveform will be distorted, resulting in an increase in the rise time of waveform and a decrease in the magnitude. In this paper, we artificially generate the optical signal simulating the distortion along the lightning channel bottom 60 m. Using six slope-intercept methods and five percentage-of-peak methods, we analyze the influence of height-dependent distortion of the return stroke on the estimated optical return stroke speed. We show that the percentage-of-peak methods tend to underestimate the speeds, and that the slope-intercept methods, in general, but not always, first underestimate the actual speeds, and then overestimate them as the return stroke propagates upward. The deviations are more pronounced for higher actual return stroke speeds. Moreover, for an assumed constant actual return stroke speed, the estimated return stroke speeds by various methods increase with increasing heights in the channel bottom, although the increasing trends become weaker as the height increases. This artificial increase is observed from the estimated two-dimensional propagation speeds of return strokes along the lightning channel bottom 60 m in rocket-triggered lightning.
LA-MC-ICP-MS dating of zircon from chromitite of the Archean Bangur Gabbro Complex, Orissa, India – Ambiguities and constraints

The Mesoarchean chromitites in the Singhbhum craton provide the main source of chromium in India. We report here results of dating zircon grains that were found in the chromitite of ultramafic rocks belonging to the southern part of the Archean Baula Complex. The chromite-bearing ultramafic rocks are cut by a gabbronorite intrusion, which had earlier been dated by SHRIMP at 3.12Ga. We have performed isotopic analysis of the zircon grains by Laser Ablation Multicollector Inductively Coupled Plasma Mass Spectrometry (LA-MC-ICP-MS) and obtained an age of 2.84Ga, which is inconsistent with the previous age reported for the gabbronorite. We have also determined the Pb isotopic composition of galena found in the chromitite and found out it was highly radiogenic given the Archean age of its host rock. We discuss the potential reasons for these results, such as later Neoarchean or even Proterozoic tectono-magmatic/hydrothermal events, and stress the importance of future detailed petrographic, mineralogical and isotopic studies to solve the dilemmas.
Objective identification and tracking of multicentre cyclones in the ERA‐Interim reanalysis dataset

We present a novel cyclone identification and tracking method that explicitly recognizes ‘multicentre cyclones’ (MCCs), defined as a cyclonic system with two or three sea‐level pressure minima within its outermost contour. The method allows for the recognition of cyclone merger and splitting events in a natural way, and provides a consistent measure of the cyclone extent. Using the ERA‐Interim reanalysis dataset, we compute a climatology using this method and show that MCCs occur in about 32 of all cyclone tracks and are much more prevalent in more intense storms. We also show that the method permits reconnection of tracks that would have been spuriously split using a conventional method. We present spatial maps of cyclone mergers, splitting, genesis and lysis using the method and also compute statistics of precipitation falling within cyclones, showing that it is strongly concentrated in the most intense cyclones. Copyright © 2011 Royal Meteorological Society
High Efficiency Quasi Class-J GaN PA with 1.8-3.0GHz Bandwidth

We present a design and implementation of a broadband high efficiency GaN Power amplifier (PA). The PA is based on Class-J continuous operation principle which using a short-circuited quarter-wavelength transmission line to bias the real part of the second harmonic impedance to be zero. And then, the optimum output fundamental impedance are matched by load-pull method with no need of internal parasitic parameters of the power transistor. The designed PA is work in a quasi Class-J mode which has high efficiency. After that, a wideband low-pass network of transmission lines is applied for output matching network in order to increase bandwidth. Simulation result show that the PA achieves output power of 39-41.5dBm in 1.8-3.0GHz with 60%-75% drain efficiency.
Learning weights with STDP to build prototype images for classification

The combination of Spike Timing Dependent Plasticity (STDP) and latency coding used in a spiking neural network has been shown to learn hierarchical features. In this paper we propose a new way to classify images using an SVM. Prototype images are built from the weights learned in an unsupervised manner using STDP. The prototype images are cross correlated with the input image and the peak of the cross correlation with each prototype image is used as additional features for an SVM. The network, demonstrated on the MNIST data set, achieves 99.15% testing accuracy which is the best reported accuracy for a SNN with unsupervised training.
Radio propagation and wireless coverage of LSAA-based 5G millimeter-wave mobile communication systems

Millimeter-wave (mmWave) communications will be used in fifth-generation (5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays (LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands (e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.
Design of a High-Efficiency Wireless Charging System for Electric Vehicle

In this paper, a high-efficiency wireless power transfer (WPT) system is analyzed, designed and implemented for electric vehicle. The silicon carbide (SiC) MOSFETs and diodes are used to reduce switching and conduction losses. The spiral coils for wireless charging is designed with finite element method. The series-series (S-S) compensation is employed to reduce impedance and increase efficiency. A 1.5-kW prototype is implemented with a 120-mm air gap to validate the proposed design scheme. Experimental results show that efficiency of the system from input DC side to output DC side is 95.6% with 1.5-kW output power and 85-kHz operating frequency. These practical measurement results have verified the effectiveness of the proposed system.
Hyperdimensional Bayesian Time Mapping (HyperBaT): A Probabilistic Approach to Time Series Mapping of Non-Identical Sequences

A common problem in time series analysis is mapping the related elements between two sequences as they progress in time. Methods such as dynamic time warping (DTW) have good performance in mapping time series signals with repeated (warped) elements relative to a reference signal. However, there is not an adequate method for mapping time series signals with inserted or deleted elements. This paper introduces hyperdimensional Bayesian time mapping (HyperBaT), a machine learning algorithm that maps two time sequence signals that may contain inserted, deleted, or warped elements. In addition, HyperBaT estimates the common underlying signal shared between the two sequences. The algorithm is presented in a general context so that it can be used in a variety of applications. There are many relevant areas, including speech processing, genetic sequencing, electronic warfare, communications, and radar processing that process signals containing inserted or deleted elements. In this paper, the performance of HyperBaT and DTW are compared using simulated signals containing inserts. For sequence mapping and classification, the performance of HyperBaT exceeds that of DTW in nearly all test cases. As an experimental example, HyperBaT is used to map radio frequency side-channel signals emitted from the processor of a computing device, in order to track control flow execution and monitor for malicious activity. Another experimental example uses HyperBaT for speaker identification.
Foraging and hoarding efficiency in buckfast purebreds and Norwegian black bee [A.m.mellifera] hybrids. Part 2. Comparison with the Caucasian bee hybrids under flying cage and laboratory test conditions

Three genetically different bee groups: Buckfast (Bcf), crossbreeds derived from mating Norwegian queens (A. mellifera mellifera) with Caucasian drones (Nor x Cau) and hybrids derived from mating Caucasian queens with Carniolan drones (Cau x Car) were compared for their ability to forage and store sugar food in field tests under flying cages and in laboratory tests. Cau x Car were used as reference/background for the former two groups. In the field trial, Cau x Car foraged the greatest amount of syrup followed by Bcf and Nor x Cau. The same results were obtained when the collection of candy by caged bees was evaluated in the laboratory. The amount of syrup foraged by bees bore no relationship to its amounts hoarded in the combs nor to the amount of candy collected in the laboratory. The greatest amount of supplies were hoarded by Bcf to be followed by Cau x Car and Nor x Cau. It was because Bcf processed the greatest amount of foraged syrup into stores and Nor x Cau were superior to Cau x Car, the latter being the worst performing sugar syrup hoarders. Bcf bees can be recommended for use and their performance can be due, to a large extent, to their general combining ability. In Norwegian bees specific combining ability can be a factor of much importance.
SiC-SiC temporary bonding compatible with rapid thermal annealing at 1000 °C

A SiC-SiC temporary bonding compatible with rapid thermal annealing at $\sim 1000^{\circ } \mathrm{C}$ has been realized. Two SiC wafers were bonded at room temperature via an intermediate Ni nano-film. After the rapid thermal annealing, the bonding was dramatically weakened and the de-bonding could be achieved at the interface. The mechanisms of this temporary bonding method has been investigated through interface analyses.
Investigations into the antioxidant and anti-inflammatory potentials of the ethanolic extract of Citrus sinensis , Linn. (sweet orange) stem-bark

This study was designed to investigate the antioxidant and anti-inflammatory potentials of the ethanolic extract and fractions of Citrus sinensis stem-bark, investigate and to evaluate the hepatoprotective potential of the most active fraction (EAF) of the ethanolic extract against acetaminophen-induced acute hepatic injury. The ethanolic extract and the fractions were screened for their secondary metabolites using established methods. The total phenolics and total flavonoid contents of the ethanolic extract and the fractions the antioxidant capacities namely DPPH radical scavenging assay, Ferric reducing power (FRAP) assay, Total antioxidant assay, Nitric oxide inhibitory assay and ABTS (2, 2-azino-bis-(3- ethylbenzothiazoline-6-sulphonic acid) radical scavenging assay and the in vitro anti-inflammatory potential of the extract and fractions were all evaluated by established methods, Hepatoprotective potential of the ethyl acetate fraction was carried out by administering the EAF and standard drug Legalex 70 (Silymarin) (p.o) for 7 consecutive days. The phytochemical screening showed the presence of tannins, flavonoids, terpenoids, cardiac glycosides, saponins and alkaloids in the extract and fractions. The result also showed that the ethyl acetate fraction showed the highest scavenging radical activities in Nitric oxide with an IC 50 of 68.85±1. 43μg/ml, ABTS with an IC 50 of 0.42±0.00mg/ml and FRAP value 1.48±0.02mgAA/g also indicated the ethyl acetate fraction to be the most active. Ethyl acetate fraction gave the highest phenolic content (2.03±0.04 mg GAE/g of fraction) while dichloromethane fraction showed the highest flavonoid content (0.38±0.01mgQUE/g) and DPPH scavenging radical with an IC 50 of 0.15±0.03mg/ml. In membrane stability, ethylacetate fraction also showed the highest stability of 88.69±4.17%. Additionally in the in vivo study, administration of acetaminophen showed significant changes in the level of the plasma and liver parameters measured when compared to the control group and it was indicative of liver damage. Pre-treatment with ethylacetate fraction (250 and 500mg/kg) and 50mg/kg legalex 70 for 7 days significantly (p<0.05) reduced the level of plasma marker enzyme (ALT, AST and GGT), total bilirubin and total protein. Increased antioxidant level (SOD, CAT, GPx and GSH) in liver tissue was also observed. In conclusion, it is probable that the antioxidant, anti-inflammatory and hepatoprotective ability of this plant extract could be attributed to the presence of flavonoids and tannins in the plant extract/fractions.
Synchrophasor Assisted Vulnerability Assessment of Zone 3 Distance Relays during Power System Stressed Condition

Analyses of the recent blackout worldwide demonstrates the contribution of zone 3 of distance relays in expanding the cascading outages in 75% of major wide area disturbances. Vulnerability assessment can be used as a useful approach for preventing of cascading outages by early detection of the critical relays which may be incorrectly operated in power system stressed conditions such as load encroachment events. In this study, in order to identify the critical relays whose maloperation can cause the cascading outages, a novel vulnerability index is introduced based on the relay margin and its sensitivity to power flow. Based on the relay operation margin sensitivity to flowing power of the protected line, a control method to increase the relay margin of the critical relay is also proposed. A novel supervisory index based on synchrophasor measurements is proposed to monitor the vulnerable distance relay to prevent its contribution in expanding the cascading outages. The efficiency and capability of the proposed approach is evaluated on IEEE-39 Bus test system and the obtained results confirm the effectiveness of the proposed method.
Leader-Following Output Consensus for High-Order Nonlinear Multi-Agent Systems by Distributed Event-Triggered Strategy via Sampled Data Information

In this paper, the observer-based leader-following output consensus problem is investigated for high-order nonlinear multi-agent systems with a distributed event-triggered mechanism. The system dynamics are described as a strict-feedback form and satisfy the Lipschitz condition. Both the event-triggered communication scheme and the sampled-based communication scheme are considered to solve the output consensus problem. First, a distributed event-triggered strategy is developed by using the dynamic output-feedback control method for the event-triggered communication scheme. With the complicated event-triggered strategy, some critical techniques are used to achieve that all the sampling intervals have a positive lower bound. Thus, Zeno behavior is excluded. Then, an event-triggered output consensus protocol is proposed with a sampled-based monitoring scheme, where the monitoring instants only happen at the sampling instants. By using the Lyapunov stability theorem, it is proved that all the output tracking errors converge to zero exponentially when the design parameters are chosen properly for both these two cases. Also, we get that it does not need all agents to be triggered synchronously. Finally, the two simulation examples are considered to show the efficiency of the consensus protocols.