Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial-temporal Analysis of Precipitation and Drought in the Poyang Lake Basin during 1957-2012

ABSTRACT Xiao, L.Y. , 2020. Spatial-temporal analysis of precipitation and drought in the Poyang lake basin during 1957-2012. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 379-382. Coconut Creek (Florida), ISSN 0749-0208. Droughts have presented an increasing trend in the Poyang Lake Basin in the past several decades. To find patterns of meteorological drought, spatiotemporal changes in precipitation and drought were analyzed. Firstly, the Mann-Kendall method was adopted for a trend test. Results show that precipitation trends in the Poyang Lake Basin have clearly temporal and spatial distinctions. For the monthly scale, there were dry trends in May for all of the basin area, while statistically significant wet trends were found in January for nearly all the basin. Secondly, the standard precipitation index (the SPI) was calculated to characterize droughts. Analysis of the standard precipitation index at a 12-month time scale suggested that the statistically significant decreasing trends were found at Xiushui station and Ganxian station, which are located in the north and south. Results of the analysis revealed that the half part of the Poyang Lake Basin became drier during 1957-2012. Morover, we can know the decrease of precipitation in May and October may be the reason of the drought in the Xiushui and Ganxian stations.
Development of open-CV framework for minutiae Extraction and matching of fingerprints

Fingerprint Recognition is a vital method in biometric identification and verification of human beings in various domains like Security, Digital Forensics, Internet of Things (loT), and many more. Each individual human is having distinct fingerprint pattern than others, hence it is one of the most prominent and widely used method to distinguish individuals. Many research studies and solutions have been developed in biometric domain since a decade, which influences now in making the process of fingerprint recognition more optimized, faster and efficient. However, present fingerprint acquisition/recognition systems have some limitations, mainly longer computation time for fingerprint matching and evaluating the results. This paper presents a procedure for fingerprint matching that takes into account minutiae features in finger print images and the process of creating an OpenCV structure for minutiae extraction and matching of fingerprints.
Plasma Impact on Overvoltage Short-Circuit Failures in ANPC Converters

Three-level converters experience more complex short-circuit patterns than the standard four types of semiconductor failures for IGBT and / or diode. In literature, there is a special pattern described where three semiconductors in series suffer due to an overvoltage protection that interferes. This happens for saving one of the switches from or against overvoltage in certain situations. However, it is possible that plasma, the free charge carriers inside the semiconductor, is still inside a fourth one as a result of previous switching actions. This allows a second parallel path and impacts the first one. Besides, the plasma itself dissipates over time, which further changes the trend of voltages and currents for the short-circuit situation.
Longitudinal Dynamics Analysis and Autopilot Design for a fixed-wing, tactical Blended-Wing-Body UAV *

The article at hand analyzes the longitudinal flight dynamics properties of a Blended Wing Body (BWB) UAV that is based on a medium-fidelity six degree of freedom model and designs the relevant autopilot system using an H∞ output feedback methodology. Current state-of-the-art design guidelines are defined and used in the development process. The multipoint linear model analysis at the extend of the flight envelope verifies the suitability of the design, enlightens the unique flight characteristics of a BWB UAV and identifies the control difficulties encountered on this unconventional aircraft.
Implementation on benchmark of SC2LE environment with advantage actor – critic method*

Deep reinforcement learning has already surpassed human performance in many video games, which is mainly achieved with reinforcement learning algorithms based on the actor-critic framework. With the release of PySC2 reinforcement learning environment by Google DeepMind and Blizzard Entertainment, deep reinforcement learning algorithms have attracted the attention of many AI developers on StarCraft II games. In this paper, we used the advantage actor - critic algorithm to achieve the training of agents on seven mini-maps released by DeepMind, we obtain the experimental results and compare them with DeepMind’s experimental benchmark. The experimental results show that the agent trained based on the advantage actor-critic algorithm has excellent performance on SC2LE environment.
An Empirical Study of TextRank for Keyword Extraction

As a typical keyword extraction technology, TextRank has been used in a wide variety of commercial applications, including text classification, information retrieval and clustering. In these applications, the parameters of TextRank, including the co-occurrence window size, iteration number and decay factor, are set roughly, which might affect the effectiveness of returned results. In this work, we conduct an empirical study on TextRank, towards finding optimal parameter settings for keyword extraction. The experiments are done in Hulth2003 and Krapivin2009 datasets, which are two real datasets. We first remove the stop word by an open published English stop word list XPO6. And then, we extract the word stems by Porter Stemmer. Porter Stemmer is a tool which can find the stems of words with multiple variants, discard redundant information, strengthen the filtering effect, and extract the effective features of the text fully. We carry out extensive experiments to evaluate the effects of the parameters to keywords extraction, and evaluate the effectiveness of corresponding results by Precision, Recall and Accuracy. Experimental results show that TextRank shows the best performance when setting co-occurrence window size <inline-formula> <tex-math notation="LaTeX">$w =3$ </tex-math></inline-formula>, iteration number <inline-formula> <tex-math notation="LaTeX">$t = 20$ </tex-math></inline-formula>, decay factor <inline-formula> <tex-math notation="LaTeX">$c = 0.9$ </tex-math></inline-formula> and rank <inline-formula> <tex-math notation="LaTeX">$k =10$ </tex-math></inline-formula> respectively, and the results are independent of the text length.
CL-TPC: a Cross Layer Transmission Power Control protocol for Routing in WSN

In this paper, a routing protocol named CL-TPC is proposed. The protocol suggests a cross layer solution, which comprises transport, network, Medium Access Control (MAC), and physical layer of the protocol stack in order to maximize the throughput, and minimizes routing overheads. WSNs are energyconstrained networks due to availability of limited supply nonrechargeable battery. Further the effect of cross-layer solution, on routing overhead, energy consumption, throughput and endto-end delay is investigated. In the proposed solution, control packets provide information to the network layer about the current status of other layers. The routing protocol uses this information to set the transmission power at the physical layer. Simulation of CL-TPC protocol is conducted on NS3 and its performance is compared with that of AODV protocol for network sizes of 25, 50, 75, and 100. Simulation results has shown that CL-TPC has lower routing overhead for all simulated network sizes, higher throughput except for network with 25 nodes and lower end-to-end delay for network with 25 and 75 nodes when compared to AODV, while energy efficiency of both the simulated protocols is same.
Effects of climate change and habitat loss on a forest‐dependent bee species in a tropical fragmented landscape

Climate change and deforestation are suggested to be the main drivers of decline in pollinators. Forest‐dependent species are expected to be the most affected and Euglossa marianae Nemésio (Hymenoptera: Apidae), an endemic species of the highly fragmented Brazilian Atlantic Forest (AF), is believed to be declining as a consequence of human impact. Over the last 17 years, we carried out field surveys to unveil its distribution, allowing us to investigate the potential effects of global climate change on this species, from the last glacial maximum into the future, using species distribution models. Our main goals were to: (i) identify populations potentially under risk of extinction given future climate change; (ii) quantify the amount of climatically suitable and climatically stable areas for E. marianae within AF; (iii) evaluate the area that are available as natural habitat and under legal protection, in an attempt to indicate priority areas to preserve this species. The most stable areas for maintaining populations of E. marianae were located in southern Bahia and northern Espírito Santo states, a region severely affected by deforestation and with several protected areas. Climate change per se does not seem to be the major problem for E. marianae. It may constitute an indirect problem given the limited dispersal abilities of this species, however. Climatically suitable areas will probably increase southwards in the future, but the extreme fragmentation of AF adds great uncertainty as to whether the species will disperse southwards, to regions such as the ‘Serra do Mar’ in northeastern São Paulo.
WA VIS: A Web-based Augmented Reality Text Data Visual Analysis Tool

When text visualization comes into the field of MAR (Mobile Augmented Reality), some problems go with it. Firstly, the natural object in the real scene holds abundant text information. Trying to recognize the natural object as a visual element rather than a marker, make text data intuitively understand. But MAR has been restricted by mobile computing speed and capability. Until now, the limitation makes text visualization difficult to meet the users’ increasing needs in NFT (Natural Feature Tracking). Tools have been needed to recognize natural object to obtain considerable text information; even worse, being limited by a small screen of mobile, two-dimensional text visualization cannot intuitively and comprehensively present all kinds of text information, and interaction methods in text visualization are too insufficient to meet users’ needs. The main technical contribution to the work is a natural feature recognition algorithm. The work is based on WebAR (Web-based AR) and an inverse BOVW (Bag of View Words) model. Transforming the feature points matching problem into a tree search problem. Compared with conventional BOVW, inverse BOVW drastically reduces the consumption of space and time; WA VIS shortens the time cost of others ranged from 8.5% to 13.7% with accuracy in 95%. And also, WebGL (Web Graphics Library) enriches interaction methods of text visualization in three-dimensional space with MAR. The test results verified that the proposed method can effectively improve the recognition speed and accuracy of the natural image in MAR for text visualization, enrich interaction in text visualization with MAR.
Image-Based Sense and Avoid of Small Scale UAV Using Deep Learning Approach

Distance detection of target object is an important information for obstacle avoidance in many fields, such as autonomous car. When the distance of the obstacle is calculated, one can determine the potential risk of collision. In this paper, a monocular camera was utilized to get the distance from an incoming unmanned aerial vehicle (UAV) using deep learning approach. The distance detection of an UAV using You Only Look Once (YOLO) object detector was proposed in this study. The region which contain the detected UAV was processed into 100 by 100 pixel and was input into the proposed model to estimate the distance of the target object. For the proposed model, a Convolutional Neural Network (CNN) was adopted to solve the regression problem. First, the feature extraction based on VGG network was performed, and then its results was applied to the distance network to estimate distance. Finally, Kalman filter was used to improve the object tracking when YOLO detector is not able to detect UAV and to smooth the estimated distance. The proposed model was trained only by using synthetic images from animation software and was validated by using both synthetic and real flight videos.
A Comparison of Losses in Artificial and Naturally Occurring Capercaillie Nests

During 1980-84 I studied the fates of 821 artificial nests, 96 naturally occurring capercaillie (Tetrao urogallus) nests, and 12 black grouse (T. tetrix) nests at Varaldskogen, Norway. In 4 of the 5 years artificial nests with poor cover had higher loss rates than natural capercaillie nests. In 1981 natural capercaillie nests had a higher loss rate than artificial nests with poor cover. In 1981 the loss rate of natural capercaillie and black grouse nests increased as the season progressed, while the loss rate of artificial nests was constantly low. Capercaillie nests were probably detected by scent by predators most years, while predators oriented mainly by sight probably robbed most artificial nests. Loss of artificial nests was not an index to the loss of capercaillie nests. In artificial nests the losses depended on nest cover; however, natural capercaillie nests in poor cover had higher losses than nests in good cover only during 1 year. J. WILDL. MANAGE. 52(1):123-126 Many bird species suffer high nest losses. Because artificial nests are easy to make they have been used to study the causes of nest losses and predator hunting strategies (Goransson et al. 1975, Boag et al. 1984, Angelstam 1986). In some studies (Henry 1969, Dzieciolowski and Matuszewski 1982, Miiller 1985) results from experiments with artificial nests have been extrapolated to natural nests. This has been done even though the relation between losses in natural versus artificial nests has not been properly evaluated. I compared nest losses of artificial nests with losses of naturally occurring capercaillie and black grouse nests (unprepared depressions in the ground) to determine if predation on artificial nests could be used as an index to predation on natural nests. The experiment was designed to separate predators that used scent from those that mainly relied on sight to locate the prey. This study was financed by the Norwegian Directorate of Nature Conservation and T. Gotaas Fund. The study was conducted in close collaboration with P. Wegge. His help and advice were essential. B. B. Larsen, L. Kastdalen and the rest of the staff at Varaldskogen Field Station assisted in the field. K. E. Erikstad, N. C. Stenseth and P. Angelstam gave valuable comments about the manuscript. S. BondrupNielsen and R. W. Dimmick have kindly improved the language. STUDY AREA This study was conducted at Varaldskogen (60010'N, 12030'E) in Hedmark County, Norway, situated in the Middle Boreal Zone (Abrahamsen et al. 1977). Norway spruce (Picea abies) and Scots pine (Pinus silvestris) were the dominating tree species, and blueberry (Vaccinium spp.) and heather (Calluna vulgaris) dominated the ground layer. Potential egg-predators were red fox (Vulpes vulpes), pine marten (Martes martes), badger (Meles meles), stoat (Mustela erminea), weasel (Mustela nivalis), hooded crow (Corvus corone cornix), common raven (C. corax), and jay (Garrulus glandarius).
Input-Reflectionless Low-Pass Filter on Multilayered Diplexer-Based Topology

A class of input-reflectionless low-pass filter (LPF) using a multilayered diplexer-based architecture is presented. It consists of two signal-transmission parts: 1) a reflective-type LPF network built with an open-ended microstrip resonator and a shunt microstrip section and 2) a resistively terminated wide-band microstrip-to-microstrip vertical transition. Thus, based on the in-band transmission poles of the wideband transition at which the RF input signal energy not transmitted by the LPF part is dissipated by the terminating 50- $\Omega $ resistor, a higher selectivity LPF response with broadband reflectionless behavior is attained. To further increase the stopband bandwidth, as well as the attenuation levels and cut-off slope sharpness, in-series cascaded multi-LPF unit designs are engineered. The main RF operational principles and theoretical design examples of the proposed input-reflectionless LPF approach are detailed. Moreover, for practical validation purposes, a two-layered two-LPF unit microstrip prototype with extended stopband and broadband input-reflectionless characteristics is designed, fabricated, and tested.
Predicting Human Activity from Mobile Sensor Data Using CNN Architecture

Having a model for predicting motion related activities of humans have tremendous applications. Quite often a simple smartphone is enough for monitoring the liveliness of a person. This can be achieved by using Activity Recognition (AR). Smartphones are employed in a wider manner and it becomes one amongst the ways to spot the human’s environmental changes by using the sensors in smart mobile. A variety of sensors are embedded in a smartphone - for instance gyroscope, accelerometer. The contraption is demonstrated to look at the state of a person. Here, a framework Human Activity Recognition (HAR) collects the raw data from sensors and movements of humans observed using a deep learning approach. Deep learning models are proposed to spot motions of humans with plausible high accuracy by using sensed data. The performance of a framework is analyzed using Convolutional Neural Network. The act of the model is analyzed in terms of exactness and efficiency. The designed activity recognition model is manipulated to detect the activities of elderly humans at home and it can detect the activities of persons in a crowded area when the area is authorized.
Security Frameworks for Internet of Things Systems - A Comprehensive Survey

Security frameworks are playing an important role in building a robust IoT system. IoT as understood today has the challenge of varied standards, architectures and models by referring the corporate that develops different applications. But, to evaluate and benchmark the security aspects of the designed IoT application, a single methodology cannot be followed, as each of those are developed based on a different architecture. Hence, a survey is undertaken to study all the security frameworks proposed by researchers, industry and those which are just conceptual. This paper discusses about various IoT architectures, security attacks possible on layers, protocols and devices of an IoT system and finally a comprehensive survey is performed on all the security frameworks of IoT systems. Further, they are classified based on the focus or the thrust area in developing the same. Finally, this survey work is concluded by comparing the security frameworks based on few important metrics and by suggesting the required improvements in designing a generic security framework that handles majority of shortcomings in the present frameworks and practices.
An Experimental Analysis of Circulating Current Control Circuit for Output Power from Vibration Generator for Vibration including the Third Harmonics

The vibration generators based on piezoelectric elements provide very low power. This research focuses on the method for improving in the output power. The previous research proposed a circulating current control circuit for improving in output power under only single frequency. This paper numerically and experimentally shows that the proposed circuit improves the output power for the vibration including the third harmonics.
Novel Soft-Switching Interleaved Boost Converters for Renewable Energy Conversion Systems

This paper proposes new soft-switching interleaved boost converters (SSIBC) for photovoltaic power generation systems. The SSIBCs presented comprises with additional dual and single auxiliary cells. The main active switches of these converters are able to provide zero voltage switching (ZVS) and zero current switching (ZCS) operation by means of dual auxiliary and single auxiliary cells, respectively. The proposed converters are capable to reduce turn on and turn off switching power losses with their soft-switching operation and consequently, they mitigate the overall efficiency. In addition, the auxiliary switches also achieve soft-turn on and turn off operation, during the total soft-switching region of main switches. The detailed principle of operation and simulation evaluations presented in this paper validate the effectiveness and soft-switching ability of the proposed interleaved boost converters.
Reproductive responses of adult female northern bobwhite and scaled quail to nutritional stress

We compared the effects of dietary protein and energy deficiencies on northern bobwhite (Colinus virginianus) and scaled quail (Callipepla squamata) reproduction and determined if nutritional deficiencies lead to reproductive failure in quail. Captive adult female quail were fed diets that varied in protein and energy content, at both ad libitum and restricted levels. Protein and energy deficiencies led to declines in body and ovary mass, and egg production, but did not affect egg mass of either species. Although body mass and reproduction of both species were affected by protein and energy deficiencies, scaled quail were less affected. Dietary energy was more important to body mass stasis and reproduction than dietary protein in both quail. Low energy diets led to elevations in corticosterone and increased food consumption in both species. Neither species increased food consumption in response to low dietary protein. Our study supports the hypothesis that macronutrient deficiencies can lead to reproductive failures in northern bobwhite and scaled quail.
Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs

Human forensic STRs are used for individual identification but have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area similar to those of genome-wide SNP and STR studies. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long-to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. These coincided with the main bodies of water, i.e. the Adriatic/Ionian and the Aegean Seas. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising in a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.
Evaluating Interconnection Schemes for Semi-transparent Perovskite Mini-modules

This work evaluates the critical issues surrounding P1, P2, and P3 scribing for semi-transparent perovskite module integration. We find that P1 scribing procedures are well-translated from other thin-film technologies. P2 scribing is best performed with a mechanical scribe, but remains a source of series resistance. P3 scribing is found to cause an increase in scribing dead area and a potential degradation source.