Comparison Of Dt& Gbdt Algorithms For Predictive Modeling Of Currency Exchange Rates

Recently, many uses of artificial intelligence have appeared in the commercial field. Artificial intelligence allows computers to analyze very large amounts of information and data, reach logical conclusions on many important topics, and make difficult decisions, this will help consumers and businesses make better decisions to improve their lives, and it will also help startups and small companies achieve great long-term success. Currency exchange rates are important matters for both governments, companies, banks and consumers. The decision tree is one of the most widely artificial intelligence tools used in data mining. With the development of this field the decision tree and Gradient boosting decision tree are used to predicate through constructed intelligent predictive system based on it. These algorithms have been used in many stock market forecasting systems based on global market data. The Iraqi dinar exchange rates for the US dollar are affected in local markets, depending on the exchange rate of the Central Bank of Iraq and the features of that auction. The proposed system is used to predict the dollar exchange rates in the Iraq markets Depending on the daily auction data of the Central Bank of Iraq (CBI). The decision tree and Gradient boosting decision tree was trained and testing using dataset of three-year issued by the CBI and compare the performance of both algorithms and find the correlation between the data. (Runtime, accuracy and correlation) criteria are adopted to select the best methods. In system, the characteristic of artificial intelligence have been integrated with the characteristic of data mining to solve problems facing organization to use available data for decision making and multi-source data linking, to provide a unified and integrated view of organization data

COMPARISON OF DT& GBDT ALGORITHMS FOR PREDICTIVE MODELING OF CURRENCY EXCHANGE RATES

Recently, many uses of artificial intelligence have appeared in the commercial field. Artificial intelligence allows computers to analyze very large amounts of information and data, reach logical conclusions on many important topics, and make difficult decisions, this will help consumers and businesses make better decisions to improve their lives, and it will also help startups and small companies achieve great long-term success. Currency exchange rates are important matters for both governments, companies, banks and consumers. The decision tree is one of the most widely artificial intelligence tools used in data mining. With the development of this field the decision tree and Gradient boosting decision tree are used to predicate through constructed intelligent predictive system based on it. These algorithms have been used in many stock market forecasting systems based on global market data. The Iraqi dinar exchange rates for the US dollar are affected in local markets, depending on the exchange rate of the Central Bank of Iraq and the features of that auction. The proposed system is used to predict the dollar exchange rates in the Iraq markets Depending on the daily auction data of the Central Bank of Iraq (CBI). The decision tree and Gradient boosting decision tree was trained and testing using dataset of three-year issued by the CBI and compare the performance of both algorithms and find the correlation between the data. (Runtime, accuracy and correlation) criteria are adopted to select the best methods. In system, the characteristic of artificial intelligence have been integrated with the characteristic of data mining to solve problems facing organization to use available data for decision making and multi-source data linking, to provide a unified and integrated view of organization data

Topology of Pulsar Profiles (ToPP). I. Graph theory method and classification of the EPN

Some of the most important information on a radio pulsar is derived from its average pulse profile. Many early pulsar studies were necessarily based on only few such profiles. There, discrete profile components were linked to emission mechanism models for individual stars through human interpretation. For the population as a whole, profiles morphology must reflect the geometry and overall evolution of the radio emitting regions. The problem, however, is that this population is becoming too large for intensive studies of all sources individually. Moreover, connecting profiles from a large collection of pulsars rapidly becomes cumbersome. In this article, we present ToPP, the first-ever unsupervised method to sort pulsars by profile-shape similarity, using graph topology. We apply ToPP to the publicly available European Pulsar Network profile database, providing the first organised visual overview of multi-frequency profiles representing 90 individual pulsars. We find discrete evolutionary tracks, varying from simple, single component profiles at all frequencies, towards diverse mixtures of more complex profiles with frequency evolution. The profile evolution is continuous, extending out to millisecond pulsars, and does not fall in sharp classes. We interpret the profiles as a mixture of pulsar core/cone emission type, spin-down energetics, and the line-of-sight impact angle towards the magnetic axis. We show how ToPP can systematically classify sources into the Rankin empirical profile scheme. ToPP forms one of the key unsupervised methods that will be essential to explore upcoming pulsar census data such as expected by the Square Kilometer Array.Comment: Submitte

Room-Temperature Quantum Hall Effect in Graphene

The quantum Hall effect (QHE), one example of a quantum phenomenon that occur on a truly macroscopic scale, has been attracting intense interest since its discovery in 1980 and has helped elucidate many important aspects of quantum physics. It has also led to the establishment of a new metrological standard, the resistance quantum. Disappointingly, however, the QHE could only have been observed at liquid-helium temperatures. Here, we show that in graphene - a single atomic layer of carbon - the QHE can reliably be measured even at room temperature, which is not only surprising and inspirational but also promises QHE resistance standards becoming available to a broader community, outside a few national institutions.Comment: Published in Science online 15 February 200

A search for pulsars in subdwarf B binary systems and discovery of giant-pulse emitting PSR J0533-4524

Binary millisecond pulsars (MSPs) provide several opportunities for research of fundamental physics. However, finding them can be challenging. Several subdwarf B (sdB) binary systems with possible neutron star companions have been identified, allowing us to perform a targeted search for MSPs within these systems. Six sdBs with companions in the neutron star mass range, as determined from their optical light curves, were observed with the Green Bank and Westerbork radio telescopes. The data were searched for periodic signals as well as single pulses. No radio pulsations from sdB systems were detected, down to an average sensitivity limit of 0.11 mJy. We did, however, discover a pulsar in the field of sdB HE0532-4503. Follow-up observations with the Giant Metrewave Radio Telescope showed that this pulsar, J0533-4524, is not spatially coincident with the sdB system. The pulsar has a relatively low magnetic field but still emits giant pulses. We place an upper limit of three to the number of radio pulsars in the six sdB systems. The non-detections may be explained by a combination of the MSP beaming fraction, luminosity, and a recycling fraction <0.5. Alternatively, the assumption of co-rotation between the MSP and sdB may break down, which implies the systems are more edge-on than previously thought. This would shift the predicted companion masses into the white dwarf range. It would also explain the relative lack of edge-on sdB systems with massive companions.Comment: 12 pages, 8 figures. Accepted for publication in MNRA

Development and evaluation of real time RT-PCR assays for detection and typing of Bluetongue virus

Bluetongue virus is the type species of the genus Orbivirus, family Reoviridae. Bluetongue viruses (BTV) are transmitted between their vertebrate hosts primarily by biting midges (Culicoides spp.) in which they also replicate. Consequently BTV distribution is dependent on the activity, geographic distribution, and seasonal abundance of Culicoides spp. The virus can also be transmitted vertically in vertebrate hosts, and some strains/serotypes can be transmitted horizontally in the absence of insect vectors. The BTV genome is composed of ten linear segments of double-stranded (ds) RNA, numbered in order of decreasing size (Seg-1 to Seg-10). Genome segment 2 (Seg-2) encodes outer-capsid protein VP2, the most variable BTV protein and the primary target for neutralising antibodies. Consequently VP2 (and Seg-2) determine the identity of the twenty seven serotypes and two additional putative BTV serotypes that have been recognised so far. Current BTV vaccines are serotype specific and typing of outbreak strains is required in order to deploy appropriate vaccines. We report development and evaluation of multiple ‘TaqMan’ fluorescence-probe based quantitative real-time type-specific RT-PCR assays targeting Seg-2 of the 27+1 BTV types. The assays were evaluated using orbivirus isolates from the ‘Orbivirus Reference Collection’ (ORC) held at The Pirbright Institute. The assays are BTV-type specific and can be used for rapid, sensitive and reliable detection / identification (typing) of BTV RNA from samples of infected blood, tissues, homogenised Culicoides, or tissue culture supernatants. None of the assays amplified cDNAs from closely related but heterologous orbiviruses, or from uninfected host animals or cell cultures

Contrasting selective patterns across the segmented genome of bluetongue virus in a global reassortment hotspot

For segmented viruses, rapid genomic and phenotypic changes can occur through the process of reassortment, whereby co-infecting strains exchange entire segments creating novel progeny virus genotypes. However, for many viruses with segmented genomes, this process and its effect on transmission dynamics remain poorly understood. Here, we assessed the consequences of reassortment for selection on viral diversity through time using bluetongue virus (BTV), a segmented arbovirus that is the causative agent of a major disease of ruminants. We analysed ninety-two BTV genomes isolated across four decades from India, where BTV diversity, and thus opportunities for reassortment, are among the highest in the world. Our results point to frequent reassortment and segment turnover, some of which appear to be driven by selective sweeps and serial hitchhiking. Particularly, we found evidence for a recent selective sweep affecting segment 5 and its encoded NS1 protein that has allowed a single variant to essentially invade the full range of BTV genomic backgrounds and serotypes currently circulating in India. In contrast, diversifying selection was found to play an important role in maintaining genetic diversity in genes encoding outer surface proteins involved in virus interactions (VP2 and VP5, encoded by segments 2 and 6, respectively). Our results support the role of reassortment in driving rapid phenotypic change in segmented viruses and generate testable hypotheses for in vitro experiments aiming at understanding the specific mechanisms underlying differences in fitness and selection across viral genomes

Splitting of critical energies in the nn=0 Landau level of graphene

The lifting of the degeneracy of the states from the graphene $n$=0 Landau level (LL) is investigated through a non-interacting tight-binding model with random hoppings. A disorder-driven splitting of two bands and of two critical energies is observed by means of density of states and participation ratio calculations. The analysis of the probability densities of the states within the $n$=0 LL provides some insights into the interplay of lattice and disorder effects on the splitting process. An uneven spatial distribution of the wave function amplitudes between the two graphene sublattices is found for the states in between the two split peaks. It is shown that as the splitting is increased (linear increasing with disorder and square root increasing with magnetic field), the two split levels also get increasingly broadened, in such a way that the proportion of the overlapped states keeps approximately constant for a wide range of disorder or magnetic field variation.Comment: 6 figure