Miracle-dz/UniFAR-FTUs huggingface dataset:
Lognormality in ecological time series

Among ecologists, it is often believed that population abundance is lognormally distributed. To test this hypothesis, we analysed and compared 544 annual time-series of population abundance longer than 30 years (n ≥ 30). Using Khamis' modified KS test we found one-half of the long-term datasets were lognormally distributed (p-value = 0.05). Among those deviating from lognormality, the most consistent feature was that the skewness was less than that expected under the lognormal hypothesis, implying a shorter upper tail (i.e. fewer extremely high values) than expected. There was little evidence of systematic extreme heavy-tail behaviour characteristic of the Levy-stable distributions in long (n > 50 years) time series. Both the standard KS test and the Akaike information criterion (AIC) were used to compare a number of alternative distributions for goodness of fit. Distributions symmetric in logarithmic scale (lognormal and log-sech) were found to fit the data best according to the KS test. However, by the AIC the gamma distribution was most often the best model. Numbers of significant departures from lognormality varied among taxa, with insects having the highest departure from lognormality. There were also trophic differences, with herbivores deviating from lognormality more than carnivores. We found no habitat or geographic dependencies in the incidence of lognormality. The poor fit of the lognormal to real data means that it is not a good substitute for specific population dynamic and distributional information. However, being a superior universal descriptor of population abundance than other twoparameter models, it may be useful in applications where such detailed information is unavailable.
Valuing Watershed Services in Mexico’s Temperate Forests

Water resources are highly valuable in arid, semiarid, or high-altitude areas where the sources are restricted to groundwater or flash floods occurred in short periods of time. In this paper, we present a case study where water is economically valued through nonmarket valuation techniques. A follow-up review of similarly-conducted case studies in Mexico was carried out to evaluate the potential relationships that elevation, moisture index, and human development index have over the economic value of water. The main factors influencing the value of water in our case study were income, education, age, and family size. Bivariate correlations of the case studies in the country suggest that there is no a significant relationship between water value and elevation, although there is some relationship between water value, moisture index, and the human development index. Dryer areas and more developed communities tend to pay more for an improvement in current water resources conditions. These results can help decision-makers to consider regional policies aimed to improve water management conditions in semiarid and less-developed communities in Mexico.
Resolving Controller Load Imbalanced State in Multiple Controllers Based Software-Defined Network

This paper proposes a switch migration scheme to balance the load of all controllers in multiple controllers based software-defined network. Several works define the number of requested packets as a controller load. The controller needs to hold the current processing until receiving a response message from the switch before processing a new request. For this reason, the number of requested packets incorporates with the path cost is defined as a controller load. In a multiple controllers approach, a load imbalanced state is recognized if a load of one controller is biased against a load of the other controllers. In the imbalanced state, connections of some switches that belong to a controller with high load are disconnected, and the switches are reconnected to the other controllers with the lower load. This process is called a migration process. The probability of migration and the efficiency of migration are used as a decision to find a switch to be migrated and the other controller to be reconnected. The load imbalanced state is resolved but the aggregate load of all controllers may be increased. In the proposed scheme, the aggregate load of all controllers after the migration is used as an indicator to select the migrated switch and a new controller. A pair of migrated switch and controller with the minimum aggregate load is selected so that the aggregate load is reduced compared to the conventional scheme. Computer simulation result shows that the proposed scheme reduces the aggregate load, compared to the traditional scheme.
Control of Third Order Processes Using Optimized Synthesis PI Controller

In closed loop system with PI controller, the most and severe problem is peak overshoot minimization in the closed loop response and tuning the proportional plus integral (PI) controller parameters. This paper deals with the two different tuning methods for obtain the PI controller settings. These methods are used to tune the parameters of PI controller and the closed loop performances of two methods are analyzed for the control of third order processes. From the closed loop responses, the time responses are move to unstable characteristics and the process variables are oscillates due to PI parameters are tuned using Ziegler-Nichols method and direct synthesis method respectively. The control loop performance of the control of third order process is improved with optimized parameters of PI controller. In direct synthesis method, the variable parameter of PI controller is obtained with Genetic algorithm. The controller parameter of PI controller is obtained from optimized variable parameters and results are reveals that the performance of closed loop is enhanced with the elimination of peak overshoot and minimization of oscillation levels in the process variables. Simulation results are confirmation that the proposed design method is better to the Ziegler-Nichols method and direct synthesis method. Furthermore, the proposed method was applied to the control of two different categories of third order processes.
HIV Prevalence and Intimate Partner Abuse in TIV Land, North Central Nigeria

Background: Several attempts have been made to document the relationship between HIV prevalence and partner violence. However, the relationship is still not clear. This present study adopted mixed methods to examine the relationship between HIV prevalence and violence amongst intimate partners in Nigeria. Methods: The multi-stage and purposive sampling methods were used to obtain 1,621 (864 women; 757 men) respondents in four different locations for the study. Structured interviews using questionnaires human health. This study draws the attention of public health and clinical practitioners, policy makers and researchers to the co-existence of HIV prevalence and intimate partner abuse for possible intervention.
Micromechanical modeling of heterogeneous energetic materials

In this work, the mesoscale processes of consolidation, deformation and reaction of shocked porous energetic materials are studied using shock physics analysis of impact on a collection of discrete HMX crystals. High resolution three-dimensional CTH simulations indicate that rapid deformation occurs at material contact points causing large amplitude fluctuations of stress states having wavelengths of the order of several particle diameters. Localization of energy produces hot-spots due to shock focusing and plastic work near grain boundaries as material flows to interstitial regions. These numerical experiments demonstrate that hot-spots are strongly influenced by multiple crystal interactions. Chemical reaction processes also produce multiple wave structures associated with particle distribution effects. This study provides new insights into the micromechanical behavior of heterogeneous energetic materials strongly suggesting that initiation and reaction of shocked heterogeneous materials involves states distinctly different than single jump state descriptions.
LEAP: the large European array for pulsars

The Large European Array for Pulsars (LEAP) is an experiment that harvests the collective power of Europe's largest radio telescopes in order to increase the sensitivity of high-precision pulsar timing. As part of the ongoing effort of the European Pulsar Timing Array (EPTA), LEAP aims to go beyond the sensitivity threshold needed to deliver the first direct detection of gravitational waves. The five telescopes presently included in LEAP are: the Effelsberg telescope, the Lovell telescope at Jodrell Bank, the Nan\c cay radio telescope, the Sardinia Radio Telescope and the Westerbork Synthesis Radio Telescope. Dual polarization, Nyquist-sampled time-series of the incoming radio waves are recorded and processed offline to form the coherent sum, resulting in a tied-array telescope with an effective aperture equivalent to a 195-m diameter circular dish. All observations are performed using a bandwidth of 128 MHz centered at a frequency of 1396 MHz. In this paper, we present the design of the LEAP experiment, the instrumentation, the storage and transfer of data, and the processing hardware and software. In particular, we present the software pipeline that was designed to process the Nyquist-sampled time-series, measure the phase and time delays between each individual telescope and a reference telescope and apply these delays to form the tied-array coherent addition. The pipeline includes polarization calibration and interference mitigation. We also present the first results from LEAP and demonstrate the resulting increase in sensitivity, which leads to an improvement in the pulse arrival times.
Unusual Framework for Fault Tolerant in a Cloud Habitat utilizing ACO Algorithm

— In today's time, a distributed computing model requires overseeing loads from the different datacenters. In any case, it is difficult assignment to manage deal with the heaps. Since, there are many issues, which are prepared to welcome issues into the mists or datacenters. It is very much characterized that there are numerous predefined calculations to deal with the issues and those are perceived by fault tolerant calculations. Yet, there are couple of calculations, which cannot manage the deficiencies. In spite of the way that, there are various frameworks which are used to get the best possible occurs for persevering through the issues. Adaptation to non-critical failure implies a technique to framework outline that allows a framework to continue performing really, when one of its parts crashes and burns or it can be characterized as limit of a framework to respond agilely to a surprising gear or programming separate. If not operational, adaptation to non-critical failure arrangements may permit a framework to keep working at lessened limit as opposed to closing down totally taking after a disappointment. Along these lines, to keep from such issues or faults, this paper concentrated on showing a structure of new fault tolerant calculation, which depends on Ant Colony Optimization strategy. ACO takes after its working in light of insect's practices and which is finding the briefest way between their settlements and a wellspring of sustenance. That is by; ACO turns into a simple and valuable method .
Root Cause Detection for Excess Control Rod Vibration in Fuel Injection Pump Using Shainin Methodology

Fuel Injection Pump (FIP) is one of the important component of any engine and any issue related to FIP will directly affect the engine. One such issue is excess vibration at full load in multi-cylinder fuel injection pump. Many problem-solving techniques are used in manufacturing industries to reduce rejection rate caused in production line and to improve quality of a product. This study mainly focuses on shainin methodology integrated with six sigma DMAIC, in which various steps were followed to detect and validate the root cause for causing excess vibration of control rod in A-type fuel injection pump.
TITLE : Neutron Scattering Studies of Spin Glass Behaviour in LiNi 02

We have performed time-of-flight neutron scattering measurements on two polycrystalline samples of LiNi02 using the Disk Chopper Spectrometer at the NIST Center for Neutron Research. These measurements reveal an absence of magnetic Bragg peaks, indicating a lack of magnetic order down to 1. 7K. In addition, we observe a significant narrowing in the width of the inelastic scattering at T 9 rv 9K, which is accompanied by a simultaneous increase in the intensity of the elastic magnetic scattering. This provides direct evidence of a spin glass transition at T 9 , implying that the low temperature magnetic state of LiNi02 is composed of frozen, disordered moments. Similar time-of-flight studies performed on NaNi0 2 , the isostructural sister compound of LiNi02 , have shown the existence of a simple magnetic structure below TN rv 23K, consisting of ferromagnetic sheets of spin 1/2 moments stacked in an antiferromagnetic fashion [1]. From the distinct similarities observed between the inelastic magnetic scattering in LiNi02 and paramagnetic NaNi02 , it is implied that the low IQI spin response in LiNi02 may originate from the collapse of short-lived spin wave modes below the (0,0,1/2) position, the lowest wave vector of antiferromagnet ic ordering. It is suggested that inherent chemical disorder in LiNi02 , caused by the substitution of Ni3+ and Li+ ions within the crystal structure, results in the frustrat ion of inter-layer magnetic interactions, thereby preventing the development of a magnetically long range ordered state.
COMPARISION OF LINEAR PARAMETRIC MODELS FOR PREDICTING FMRI RESPONSE by Parina Gandhi

COMPARISION OF LINEAR PARAMETRIC MODELS FOR PREDICTING FMRI RESPONSE by Parina Gandhi In this study, five different linear parametric models including Autoregressive model (ARX), Autoregressive Moving Average Model (ARMAX), Box-Jenkins Model (BJ), Instrument Variable Model (IV) and Prediction Error Model (PEM) were used to predict the fMRI response and their performances compared. Transfer functions were computed for every voxel time series for every subject using all the parametric models. Crosscorrelation was subsequently performed between the predicted response and the actual fMRI data to compare the performance of the five models. The consistency of the models and the transfer function was checked by doing a statistical analysis. Among the five models tested, PEM resulted in the highest correlation coefficient of 0.76 with the measured response, while ARX, which was the simplest of all, gave the least correlation coefficient of 0.23 with the measured response. The PEM model was consistent in predicting the response between the subjects compared to all other models. A significant difference between the PEM model versus the other models was observed for all the subjects.
Design of LVDS Transmitter with SLVDS mode for Low Power Applications in 55nm CMOS Technology

This paper presents the design of Low voltage differential signaling (LVDS) transmitter with Sub LVDS (SLVDS) mode for low power applications. The proposed design works for supply voltage of 1.8V with an output voltage swing of 350mV over 1.2 V offset in LVDS mode and a supply voltage of 1.5V with an output voltage swing of 150mV over 0.9V offset in SLVDS mode. A pre-emphasis circuit which inject current only during data transition is also proposed to support high speed transmission. This design is implemented in 55nm CMOS technology to work across PVT corners and is simulated using Cadence Virtuoso. This design achieves data rate of 1 Gb/s and 2 Gb/s in SLVDS and LVDS modes respectively and power consuption in SLVDS mode is under 10 mW.
Bots detection by Conformal Clustering

Botnets, networks of infected machines controlled by an attacker, are a widespread and dangerous threat over the Internet, since they are used to perform most of the malicious activities such as distributed denial of service attacks (DDoS), phishing or spamming. This project aims at detecting botnet infected machines (bots) by analysing high level network tra c features (NetFlow data). Specifically, our main goal in this scenario is to detect previously known botnets, and to cluster together similar kinds of them. We approach the problem by using Conformal Clustering, a clustering method based on Conformal Prediction, where significance level is used to trim the hierarchy of clusters. This report introduces a few novel aspects to previous research, such as a substantial and motivated increase of the feature set, a feature evaluation algorithm to apply before clustering (SIM-DIFF ), an algorithm for periodicity detection by using Partial Autocorrelation Function (PACF) instead of Discrete Fourier Transform (DFT), and the use of Purity as an accuracy criterion for Conformal Clustering. The use of NetFlow informations makes our approach reliable even when the tra c within the botnet is encrypted. This report also documents the creation of a Python package as an implementation of our work. This code has a structure which can be easily used and extended for future research.
An evaluation of ambient ammonia concentrations over southern Ontario simulated with different dry deposition schemes within STILT-Chem v0.8

Abstract. A bidirectional air–surface exchange scheme for atmospheric ammonia was incorporated into the Stochastic Time-Inverted Lagrangian Transport air quality model (STILT-Chem v0.8). STILT-Chem v0.8 was then applied to simulate atmospheric ammonia concentrations at 53 measurement sites in the province of Ontario, Canada for a six-month period from 1 June to 30 November 2006. In addition to the bidirectional scheme, two unidirectional dry deposition schemes were tested. Comparisons of modeled ammonia concentrations against observations show that all three schemes can reasonably predict observations. For sites with low observed ammonia concentrations, the bidirectional scheme clearly overestimated ammonia concentrations during crop-growing season. Although all three schemes tended to underestimate ammonia concentrations after mid-October and for sites with elevated observed concentrations, mainly due to underestimated NH3 emission inventory after mid-October and/or underestimated emission potentials for those sites, the bidirectional scheme performed better because of its introduction of compensation points into the flux calculation parameterization. In addition to uncertainties in the emission inventory, the results of additional sensitivity tests suggest that uncertainties in the input values of emission potentials in the bidirectional scheme greatly affect the accuracy of modeled ammonia concentrations. The use of much larger emission potentials in the bidirectional scheme and larger anthropogenic NH3 emission after mid-October than provided in the model emissions files is needed for accurate prediction of elevated ammonia concentrations at intensive agricultural locations.
Design and analysis of planar ultra-wideband antenna with dual band-notched function

A novel planar ultra-wideband (UWB) antenna with dual band-notched characteristics is proposed. The antenna is fabricated on a printed circuit board (PCB), having a circular monopole and arc-shaped parasitic strips on one side and a ground plane with a slot aperture on the other side. Two narrow bands at 5.15-5.35 GHz and 5.725-5.825 GHz are notched by using two arc-shaped parasitic strips on the same layer of the radiator. Compared with other band-notched UWB antennas, the proposed antenna exhibits the advantages of simple structure, compact size, simple control of each notched frequency band using separate parasitic strips, and good performance. Surface current distributions and equivalent circuit model are applied to analyze the operating principle of the proposed antenna. To validate the concept, a prototype is fabricated and tested. Both simulated and measured results confirm that the proposed antenna achieves a wide bandwidth from 3.1 GHz to 10.6 GHz with two narrow bands notched successfully. The results of VSWR, radiation patterns and gain response are shown and discussed in detail. The antenna enables the independent control of the notched frequency bands, and the proposed method can be extended for designing planar UWB antennas with multiple band-notched characteristics and reconfigurable notched frequency.
Visual Localization in Changing Environments using Place Recognition Techniques

This paper proposes a visual localization system combining Convolutional Neural Networks (CNNs) and sparse point features to estimate the 6-DOF pose of the robot. The challenges of visual localization across time lie in that the same place captured across time appears dramatically different due to different illumination and weather conditions, viewpoint variations and dynamic objects. In this paper, a novel CNN-based place recognition approach is proposed, which requires no time-consuming feature generation process and no task-specific training. Moreover, we demonstrate that the rich semantic context information obtained from place recognition can greatly improve the subsequent feature matching process for pose estimation. The semantic constraint performs much better than traditional Bag-of-Words based methods for establishing correspondences between the query image and the map. To evaluate the robustness of the algorithm, the proposed system is integrated into ORB-SLAM2 and verified on the data collected over various illumination and weather conditions. Extensive experimental results show that even with weak ORB descriptors, the proposed system can significantly improve the success rate of localization under severe appearance changes.
Comparing Quality and Business Improvement Methodologies for Collaborative Working in the Product Development Process of SMEs

This paper makes the case that of all of the improvement methodologies used in businesses, continuous improvement can overcome the problem of ossification in the context of new product development where the ability to engage in exploitation and exploration may be a prerequisite for business success in the future. In particular, indicators such as linking strategic objectives to improvement activity and degrees of integration of systems within and between firms have a close fit with the cultural dimension of continuous improvement, something which is largely absent from top down, output focused TQM and Lean programmes. The case is made on the basis of a review of a variety of literatures including those on TQM, Lean, continuous innovation, the extended manufacturing enterprise and bootlegging.
An evaluation of acoustic reflectometry for leakage and blockage detection

Acoustic reflectometry has been shown to be an effective technique for detecting defects, such as holes and blockages, in relatively short, single lengths of pipe. This paper discusses briefly the physical basis of the technique and then describes the results of a series of experiments that were designed to evaluate the suitability of using this approach for monitoring the health of natural gas pipelines. Such pipelines will typically be many kilometres long, have diameters of up to 1 m and may form part of a complex network of pipelines. Previous studies have demonstrated that acoustic reflectometry techniques can be used to detect pipeline defects in relatively small bore pipelines with lengths of several hundred meters. The results reported in this paper indicate that even when using fairly crude equipment, the technique can be successfully applied to detect defects in single pipelines and pipeline networks with large diameters and lengths exceeding 5 km. Although the results presented in this paper are not conclusive, they do provide the necessary justification for a second phase of experiments to be conducted to extend the scope of the technique further.