Miracle-dz/UniFAR-FTUs huggingface dataset:
Forecasting with ARMA models

This paper employs the R software in identifying the most suitable ARMA model for forecasting the growth rate of the exchange rate between the US dollar and a unit of the British pound. The data is systematically split into two distinct periods identified as the in-sample period and the out of sample period. The best model selected for the in-sample period is used to make forecasts for the out of sample period. Both traditional and rolling window forecasting methods are employed. This research uses the MSE, MAE, MAPE and correct sign prediction criterion to compare the forecasting performance of the rolling window forecasting method and the traditional forecasting method. The results obtained suggest that the traditional forecasting method performs better judging by MSE, MAE and MAPE. In other words, the traditional forecasting method is more suitable for predicting the magnitude (i.e., size) by which the US /UK exchange rate changes over time. However, the results also suggest that the rolling window forecasting method performs better based on the correct sign prediction criterion. In other words, the rolling window forecasting method is more appropriate for predicting the changes in the sign of the US /UK exchange rate.
Development of Efficient and Secured Face Recognition using Biometrics

– With the rapid development of the computer & increasing security authentication application where virtually any environment or situation requires a key , card as passwords for access can be replaces as further enhanced by face recognition, Face recognition has reduce significant attention due to its wide range of application, not only to the public sector, such as security, surveillance and access control for offices, since a key or a card can be easily reduplicated (or lost) and a password might be cracked, So either an authorized person might not get the access.In using biometric data privacy laws, it is important for biometric data users . In biometric data safety and security, there are various modality or technology are used. Biometric methods used for this are conventional and unconventional in future.
On the suitability of second-order accurate finite-volume solvers for the simulation of atmospheric boundary layer flow

Abstract. The present work analyzes the quality and reliability of an important class of general-purpose, second-order accurate finite-volume (FV) solvers for the large-eddy simulation of a neutrally stratified atmospheric boundary layer (ABL) flow. The analysis is carried out within the OpenFOAM® framework, which is based on a colocated grid arrangement. A series of open-channel flow simulations are carried out using a static Smagorinsky model for subgrid scale momentum fluxes in combination with an algebraic equilibrium wall-layer model. The sensitivity of the solution to variations in numerical parameters such as grid resolution (up to 1603 control volumes), numerical solvers, and interpolation schemes for the discretization of nonlinear terms is evaluated and results are contrasted against those from a well-established mixed pseudospectral–finite-difference code. Considered flow statistics include mean streamwise velocity, resolved Reynolds stresses, velocity skewness and kurtosis, velocity spectra, and two-point autocorrelations. A quadrant analysis along with the examination of the conditionally averaged flow field are performed to investigate the mechanisms responsible for momentum transfer in the flow. It is found that at the selected grid resolutions, the considered class of FV-based solvers yields a poorly correlated flow field and is not able to accurately capture the dominant mechanisms responsible for momentum transport in the ABL. Specifically, the predicted flow field lacks the well-known sweep and ejection pairs organized side by side along the cross-stream direction, which are representative of a streamwise roll mode. This is especially true when using linear interpolation schemes for the discretization of nonlinear terms. This shortcoming leads to a misprediction of flow statistics that are relevant for ABL flow applications and to an enhanced sensitivity of the solution to variations in grid resolution, thus calling for future research aimed at reducing the impact of modeling and discretization errors.
Toward Emerging Cubic-Spline Patterns With a Mobile Robotics Swarm System

An innovative and flexible approach is introduced to address the challenge of self-organizing a group of mobile robots into cubic-spline-based patterns without any requirement of control points. Besides the self-organization of mobile robots, the approach incorporates a potential field-based control for obstacle/collision avoidance. This will offer more flexibility to swarm robots to efficiently deal with many practical situations, including smoothly avoiding obstacles during movement or exploring and covering areas with complex curved patterns. Essentially, this challenge is approached by proposing a formation control model based on a smoothed particle hydrodynamic estimation technique, which uses special cubic-spline kernel functions applied here to interpolate the density of each robot in the swarm. The moving information is used to weigh the distances to the robot’s neighbors available in its field of view. Then, an artificial physics mesh is finally built among each robot and its three available neighbors having the smallest weighted distances. Significant results toward emerging cubic-spline patterns are shown with a swarm of foot-bot mobile robots simulated in the ARGoS platform. Analysis results with different metrics are also conducted to assess the performance of the model with different swarm sizes and in the presence of sensory noise as well in the presence of partially faulty robots.
Serotyping of Serratia marcescens: Current Status of Seven Recently Described Flagellar (H) Antigens

The slightly revised, current scheme of 20 flagellar (H) antigens of Serratia marcescens was examined. The seven new H antigens were demonstrated to be antigenically distinct as determined with Le Minor's H-immobilization test. The H-immobilization antibodies of rabbit anti-H immune sera proved resistant to treatment with 2-mercaptoethanol and dithiothreitol, respectively. On the other hand, dual absorptions of rabbit anti-H immune sera with killed cells of Staphylococcus aureus strain Cowan I, i.e., protein A, failed to reduce significantly Himimobilization titers of rabbit sera, although human immunoglobulins G and M were bound by protein A. It was tentatively concluded that the 2-mercaptoethanoland dithiothreitol-refractory H-immobilizing rabbit antibodies belonged to the immunoglobulin M class. H-antigen (phase) variation was not demonstrable in several extramural, clinical isolates of S. marcescens for which this phenomenon had been claimed. Rather, four of these six isolates were found to consist of cell populations of two distinct serotypes, as also borne out by bacteriocin typing; the flagellar H-antigens of the remaining two isolates were stable, with minor, heterologous H-antigen cross-reactivity.
A Power Domain UFMC System Design for Underwater Optical Communication with Reduced PAPR

The Power-Domain Universal Filtered Multi-Carrier (PD-UFMC) waveform is one of the most promising technologies for the upcoming modern Underwater Optical Communication (UOC) systems due to its significant benefits in terms of bandwidth performance, massive connectivity, multi-path fading robustness and short-packed burst support. However, it is unfortunate that the PD-UFMC based UOC (PD-UFMC-UOC) waveform suffers from the high Peak-to-Average Power Ratio (PAPR) problem as it is multi-carrier in nature. Therefore, this paper introduces a new PD-UFMC-UOC waveform method based on Discrete Sine Transform (DST) precoding that is designed to solve the aforementioned problem by reducing the high PAPR. In addition, DST precoding is also capable of taking advantage of the frequency variations in the multipath UOC channel that can help to reduce the Bit Error Rate (BER). MATLAB® computer simulations were performed to demonstrate the performance as well as to evaluate the proposed PD-UFMC-UOC waveform. It is concluded by observing the simulation results that the proposed waveform outperforms the UOC waveform based on Power Domain Orthogonal Frequency Division Multiplexing (PD-OFDM) in terms of reducing the high PAPR values.
Big Data Monetization: Discoveries from a Systematic Literature Review

— This study investigated how monetization of data in a Big Data environment has been suggested in academic literature. Our goal was to find out what methods have been applied to determine the relevance and value of data in these environments and if these methods are based, in any way, on information theory. In order to come to a conclusion, we applied a formal process of systematic literature review based on the methodology suggested by Kitchenham. The results showed that, in spite of the progress made on the topics of Big Data and the application of analytical methodologies over the last decades, there is no method based on data that is widely used to determine the value of a datum in a Big Data environment. By observing the results, it is possible to conclude that little attention has been given to the dimension Value in academic studies related to Big Data when compared to searches directed to the other three classical dimensions (Volume, Velocity and Variety). More specifically, in terms of economic value, studies are even scarcer, and the existing ones do not share a common view on how to measure this value. If, on the one hand, monetization in Big Data environments is still a field that needs to be better explored in academic literature, on the other hand, these intangible assets, i.e., data, grow exponentially and are more and more present in the corporate world. It highlights the opportunity to develop studies in search of standards that can be widely accepted and used to this end.
Evaluation of anti-diabetic activity of Trianthema portulacastrum Linn in Dithizone induced diabetes in Wistar rats

Trianthema portulacastrum Linn. Whole plant is an extensively used plant for medication in India for the treatment of various health issues. This study was focused to prefigure the antidiabetic potency of Chloroform extract of the Trianthema portulacastrum (CETP) whole plant administered at two doses (100mg/kg and 200 mg/kg) for the duration of 21days in Dithizone - induced diabetic rats. The rats were separated into five groups, each group containing six animals. All Groups except Group I were made diabetic by intraperitonial administration of Dithizone(50mg/kg). Group I served as control group, Group II served as diabetic control received Dithizone(50mg/kg), Group III rats were administered with glibenclamide (10mg/kg), a standard oral hypoglycemic agent while Group IV and Group V diabetic rats were served with 100 mg/kg and 200 mg/kg of CETP whole plant respectively. Potency of the plant extract as an antidiabetic was assessed in dithizone induced diabetic models by comparing biochemical parameters like blood glucose level, Glucose tolerance, lipid profiles along with the liver antioxidant enzymes, glycogen content and Glycogenic enzymes which were quantified using standard experimental procedures. There exists a significant reduction in levels of blood glucose, raise in glucose tolerance, and improved imbalance in lipid metabolism in diabetic rats after administration of the extract at 100mg/kg and 200mg/kg. T.portulacastrum with 200mg/kg of the extract showed the best hypoglycemic action by comparing favorably well with Glibenclamide. This investigation clearly showed that, the extract is endowed with hypoglycemic activity, T.portulacastrum may also defend the deterioration of liver due to diabetes.
Asymmetric Routing in Constrained Mobility Networks

We revisit the age-old question of maintaining routes in the context of a campus area network where mobile devices multi-hop to access one or more resource-rich base stations. In this constrained-mobility and asymmetric environment, we ﬁnd that as the network density increases, the average time for a mobile device to lose connectivity to all of its neighbors grows much faster than the minimum time to lose connectivity to all of its neighbors. This leads us to consider routing where (a) route update decisions are mobility aware, (b) path maintenance of devices is event-driven rather than periodic, (c) a device can choose from several neighbors to forward its messages, and (d) route repair is ofﬂoaded to base station(s). We compare the resulting braided multi-path tree protocol, which we call Asymmetric mobility-Event driven Routing (AER) , with multi-path variants of the classic DSDV, OSPF, and Bellman-Ford protocols. Through both analysis and simulation, we ﬁnd that AER outperforms the others for most of the low mobility region.
An Ensemble Approach for Clustering Protein-Protein Interaction Networks

Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in PPI networks has been theorized by many researchers. However, PPI networks are known to contain noisy false positive interactions and possess the scale-free property, which makes the task of isolating these useful modules dif(cid:2)cult. In this paper, we propose an ensemble clustering approach to address this problem. To perform initial clustering, we examine three topology-based distance metrics that are conducive for partitioning these networks. To perform consensus clustering, we develop a PCA-based hyper-graph approach, designed to handle large interaction networks. We also develop a soft consensus clustering method to assign multifaceted hub proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-speci(cid:2)c validation metrics and show that our approaches can provide signi(cid:2)cant bene(cid:2)ts over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can a) produce improved biologically signi(cid:2)cant functional groupings; and b) facilitate soft clustering by discovering multiple functional associations for hub proteins.
Real‐time predictive eco‐driving assistance considering road geometry and long‐range radar measurements

Eco-driving assistance systems incorporating predictive or feedforward information are a promising technique to increase energy-efﬁciency and reduce CO 2 emissions from road transportation. This work gives details of such a system that was recently developed by the authors, which uses real-time data from GPS and automotive radar to perform a predictive optimisation of a vehicle’s speed proﬁle and coaches a driver into fuel-saving and CO 2 -reducing behaviour. A repeated-measures study carried out in a ﬁxed-base driving simulator indicated an overall reduction in fuel consumption of 6 . 09 % , which was signif-icantly greater than improvements expected from reductions in average speed. Adjusted for average speed, fuel-efﬁciency improvements when using the system are similar to those observed in unassisted eco-driving, but with improvements in travel time in motorway situations. Finally, an on-road prototype is described in which the optimisation is solved using data from vehicle sensors, successfully demonstrating that real-time implementation of the system is feasible.
Identification of nucleotide variation of growth hormone gene in rabbit populations reared in Bulgaria

Five rabbit populations of New Zealand White (NZW), Californian (CAL), crossbred NZW×GW and two generations of the synthetic population – SPF1 and SPF2 reared in Bulgaria were included in the present study with the aim of detecting the genetic variability of the growth hormone encoding gene (GH) via polymerase chain reaction with the restriction fragment length polymorphism analysis and direct sequencing. The targeted region of the rabbit GH gene was amplified and a fragment of a total of 231 bp was obtained in all studied populations. Allele identification was determined after enzymatic digestion, where two fragments of 62 and 169 bp correspond to allele C and an undigested fragment of 231 bp corresponds to allele T. Two additional bands of 107 and 124 bp evidenced A/G genetic polymorphism in the rabbit GH gene. Thirtyeight percent of the studied rabbits were carriers of the double mutation (C/T+A/G) in the same locus as the studied GH gene. The sequence analysis revealed two nucleotide substitutions – g.111C>T and g.156A>G in the non-coding region between the regulatory TATA box and 5’ UTR region, and a novel g.255G>A genetic variant in intron 1 of GH gene. The A>G transition was most frequent (40.57%), compared to the other ones, G>A (28.57%) and C>T (10.80%), respectively. The most frequent genotype in the NZW population was homozygous TT (0.93), with a prevalence of the T allele (0.97) over allele C (0.03) for g.111C>T SNP site. The distribution of the allele and genotype frequencies at the sites g.156A>G and g.255G>A in this rabbit group was identical, with the highest value of 0.93 for alleles A and G, respectively. The rabbit populations CAL and NZW×GW showed equal frequencies of the prevalent T allele (0.83) and for homozygous TT genotype (0.67) according to g.111C>T SNP. The highest values were obtained for the allele А (0.83) and for homozygous AA genotype (0.67) at c.33A>G SNP in these rabbit groups. The highest values (0.67, 0.60 and 0.80) for the heterozygous genotypes at g.111C>T, g.156A>G and g.255G>A SNPs, respectively, were detected among the SPF2 rabbit population, compared to the both homozygous genotypes. The results obtained in the present research indicates a significant degree of genetic variability of the studied polymorphic GH locus in the SPF2 rabbit group.
Low-light images enhancement method in coal mine based on knowledge distillation

In order to solve the problems of low illumination and poor image quality in video monitoring systems caused by complex lighting conditions in underground mines, a low-light image enhancement method based on knowledge distillation is proposed. By establishing Net-S (student network) and Net-T (teacher network) for feature simulation, this method improves the image reconstruction ability of the model while transferring knowledge and improves the network efficiency and image enhancement effect at the same time. The improved RIR (residual in residual blocks) module is added to improve the feature extraction ability of the model. At the same time, the loss function for low illumination image characteristics is designed to improve the accuracy of the network model in image reconstruction. Compared with the traditional knowledge distillation network model, Net-T and Net-S of the model output different images respectively. Net-T extracts features from high-quality images. Net-S simulates features under the guidance of Net-T, and finally obtains enhanced images. The experimental results show that the model can effectively remove part of the noise, improve the brightness and quality of the image, and improve the visual effect of the image. Moreover, the model has good generalization ability. Compared with CLAHE and LIME, the absolute cumulative change of the normalized objective index of this method is increased by 42.21%, 7.47% and 30.18% respectively. In view of the low illumination image enhancement of the mine, this method has certain advantages, which can significantly improve the overall brightness of the image, reduce the noise, and is more in line with the human visual perception. To a certain extent, it meets the needs of the construction of intelligent mine video monitoring system.
Overview of Federal Law and USEPA Regulations for Urban Runoff

Within the last three years, the United States Environmental Protection Agency (USEPA) has taken two significant steps with respect to regulating the quality of storm water discharges from urban areas. The first of these is the development of Final Rules and Regulations for Storm Water Discharges from urban areas with separated waste water and storm drainage systems. Published in late 1990, the rule requires all municipalities with populations over 100,000 to apply for a permit to discharge storm water under the USEPA9s National Pollutant Discharge Elimination System (NPDES). The permit application must include, among other things, a plan to reduce the pollutants in urban runoff to the “Maximum Extent Practicable”. The second step is the publication in January, 1993, of a draft policy regulating discharges from combined sewer systems. These two initiatives for water quality control of wet weather discharges from urban drainage systems are significant steps forward in a national program to reduce pollution contributions to receiving waters in urban areas. This paper provides an overview of the requirements of these two wet weather water quality management programs.
FROM PLANNING TO REGULATION: TOWARD A NEW DIRIGISME?

In this article in honor of Professor BR. Shenoy, the preeminent classical liberal Indian economist during the lost years of Indian planning, I will discuss the “new dirigisme” that is emerging even as there is aworldwide move from the plan to the market. The dirigiste impulse has notbeen stifled but merely transformed from planning that sought tosupplant the price mechanism toregulation that seeks tosupplement it. The intellectual basis for both sorts of dirigisme is the same. Planning being discredited by the events of 1989, dirigistes—spanning the political spectrum—have rallied around the banner ofbureaucratic regulation to correct various forms ofperceived market failure. These relate to externalities, in particular those relating to the environment, and to various forms of monopoly. Having dealt with the former elsewhere (see Lal 1994, 1995), I shall be mainly concerned with the latter. This new metamorphosis of the dirigiste beast—in the form of bureaucratic regulation of the market—has plagued the United States since World War II. In particular, given the growing importance and shortage of infrastructure—and the inability to finance it through taxation—governments in both the Third and Second Worlds are being forced to examine private sector alternatives. As many aspects of infrastructure have the characteristics of natural monopolies, which current wisdom and past practice in the United States deem require regulation in “the public interest,” its future development and regulation will provide the major operational arena for the new dirigisme.
Gender-induced teacher stereotypes on the awareness and conscious use of pedagogical gestures as enhancement technique among English teachers in secondary schools in Enugu state, Nigeria

The study seeks to ascertain the awareness and conscious use of language teachers on pedagogical gestures and whether gender-induced teacher stereotypes influence teachers’ awareness and conscious use of pedagogical gestures. The study adopts the survey research design with a sample size of 262 drawn using multi-staged sampling techniques. The Z-test method was used in testing the hypothesis of the study. It was discovered that there was high mean response of teachers on the awareness of general purpose gestures and pedagogical gestures. There were significant differences in the mean response of male/female teacher’s awareness of pedagogical gestures as enhancement technique, and no significant differences in the mean response of male/female teacher’s conscious use of pedagogical gestures as enhancement technique. Our conclusion is that pedagogical gestures are indispensable in lesson delivery and that their pedagogic values are gained through awareness and conscious use of them as enhancement technique. The study recommends practical training of teachers on the use of pedagogical gestures as a regular exercise and teachers’ assessment in the use of pedagogical gestures be made part of teacher promotion examinations in Nigeria to encourage conscious use of the gestures.