484 research outputs found
A comparative study of selected classification accuracy in user profiling
In recent years the used of personalization in service provisioning applications has been very popular. However, effective personalization cannot be achieved without accurate user profiles. A number of classification algorithms have been used to classify user related information to create accurate user profiles. In this study four different classification algorithms which are; naive Bayesian (NB), Bayesian Networks (BN), lazy learning of Bayesian rules (LBR) and instance-based learner (IB1) are compared using a set of user profile data. According to our simulation results NB and IB1 classifiers have the highest classification accuracy with the lowest error rate
Classification accuracy performance of Naïve Bayesian (NB), Bayesian Networks (BN), Lazy Learning of Bayesian Rules(LBR) and Instance-Based Learner (IB1) - comparative study
In recent years the used of personalization in service provisioning applications has been very popular. However, effective personalization cannot be achieved without accurate user profiles. A number of classification algorithms have been used to classify user related information to create accurate user profiles. In this study four different classification algorithms which are; naive Bayesian (NB), Bayesian networks (BN), lazy learning of Bayesian rules (LBR) and instance-based learner (IB1) are compared using a set of user profile data. According to our simulation results NB and IB1 classifiers have the highest classification accuracy with the lowest error rate. The obtained simulation results have been evaluated against the existing works of support vector machines (SVMs), decision trees (DTs) and neural networks (NNs)
Measurement of Liquid Velocity and Liquid Distribution in a Packed Bed Using Electrical Resistance Tomography
Optimization of supercritical extraction of nimbin from neem seeds in presence of methanol as co-solvent
Mathematical modeling and optimization of the extraction of nimbin from neemseeds using supercritical carbon dioxide with methanol as co-solvent is the subject of this study. At first a correlation for Sherwood number (Sh) as a function of Reynolds number (Re) and Schmidt number (Sc) was proposed using a Genetic Algorithm (GA) technique. This correlation was compared to previous correlations and was found to give the most accurate results. Moreover, optimum conditions (temperature, pressure, solvent flow rate and particle diameter) which maximizes the extraction yield have been determined using GA. At the next step, methanol was used as a co-solvent and the dynamic equilibrium constant of solute between the solid phase and the solvent was estimated. By applying the new determined equilibrium constant, good agreement between the model and experimental data was observed
Absence Seizures as a Feature of Juvenile Myoclonic Epilepsy in Rhodesian Ridgeback Dogs
Myoclonic epilepsy in Rhodesian Ridgeback (RR) dogs is characterized by myoclonic seizures occurring mainly during relaxation periods, a juvenile age of onset and generalized tonic-clonic seizures in one-third of patients. An 8-month-old female intact RR was presented for myoclonic seizures and staring episodes that both started at 10 weeks of age. Testing for the DIRAS1 variant indicated a homozygous mutant genotype. Unsedated wireless video-electroencephalography (EEG) identified frequent, bilaterally synchronous, generalized 4 Hz spike-and-wave complexes (SWC) during the staring episodes in addition to the characteristic myoclonic seizures with generalized 4-5 Hz SWC or 4-5 Hz slowing. Photic stimulation did not evoke a photoparoxysmal response. Repeat video-EEG 2 months after initiation of levetiracetam treatment disclosed a >95% decrease in frequency of myoclonic seizures, and absence seizures were no longer evident. Absence seizures represent another seizure type in juvenile myoclonic epilepsy (JME) in RR dogs, which reinforces its parallels to JME in humans.Peer reviewe
Diagnostic Utility of Wireless Video-Electroencephalography in Unsedated Dogs
Background: Poor agreement between observers on whether an unusual event is a seizure drives the need for a specific diagnostic tool provided by video-electroencephalography (video-EEG) in human pediatric epileptology. Objective: That successful classification of events would be positively associated with increasing EEG recording length and higher event frequency reported before video-EEG evaluation; that a novel wireless video-EEG technique would clarify whether unusual behavioral events were seizures in unsedated dogs. Animals: Eighty-one client-owned dogs of various breeds undergoing investigation of unusual behavioral events at 4 institutions. Methods: Retrospective case series: evaluation of wireless video-EEG recordings in unsedated dogs performed at 4 institutions. Results: Electroencephalography achieved/excluded diagnosis of epilepsy in 58 dogs (72%); 25 dogs confirmed with epileptic seizures based on ictal/interictal epileptiform discharges, and 33 dogs with no EEG abnormalities associated with their target events. As reported frequency of the target events decreased (annually, monthly, weekly, daily, hourly, minutes, seconds), EEG was less likely to achieve diagnosis (P <0.001). Every increase in event frequency increased the odds of achieving diagnosis by 2.315 (95% confidence interval: 1.36-4.34). EEG recording length (mean = 3.69 hours, range: 0.17-22.5) was not associated (P = 0.2) with the likelihood of achieving a diagnosis. Conclusions and Clinical Importance: Wireless video-EEG in unsedated dogs had a high success for diagnosis of unusual behavioral events. This technique offered a reliable clinical tool to investigate the epileptic origin of behavioral events in dogs.Peer reviewe
Metabolomic serum abnormalities in dogs with hepatopathies
Hepatopathies can cause major metabolic abnormalities in humans and animals. This study examined differences in serum metabolomic parameters and patterns in left-over serum samples from dogs with either congenital portosystemic shunts (cPSS, n = 24) or high serum liver enzyme activities (HLEA, n = 25) compared to control dogs (n = 64). A validated targeted proton nuclear magnetic resonance spectroscopy platform was used to assess 123 parameters. Principal component analysis of the serum metabolome demonstrated distinct clustering among individuals in each group, with the cluster of HLEA being broader compared to the other groups, presumably due to the wider spectrum of hepatic diseases represented in these samples. While younger and older adult control dogs had very similar metabolomic patterns and clusters, there were changes in many metabolites in the hepatopathy groups. Higher phenylalanine and tyrosine concentrations, lower branched-chained amino acids (BCAAs) concentrations, and altered fatty acid parameters were seen in cPSS dogs compared to controls. In contrast, dogs with HLEA had increased concentrations of BCAAs, phenylalanine, and various lipoproteins. Machine learning based solely on the metabolomics data showed excellent group classification, potentially identifying a novel tool to differentiate hepatopathies. The observed changes in metabolic parameters could provide invaluable insight into the pathophysiology, diagnosis, and prognosis of hepatopathies.Peer reviewe
Assembly and Analysis of Unmapped Genome Sequence Reads Reveal Novel Sequence and Variation in Dogs
Correction Volume: 8, Article Number: 11853 DOI: 10.1038/s41598-018-30169-3 Published:AUG 2 2018Dogs are excellent animal models for human disease. They have extensive veterinary histories, pedigrees, and a unique genetic system due to breeding practices. Despite these advantages, one factor limiting their usefulness is the canine genome reference (CGR) which was assembled using a single purebred Boxer. Although a common practice, this results in many high-quality reads remaining unmapped. To address this whole-genome sequence data from three breeds, Border Collie (n = 26), Bearded Collie (n = 7), and Entlebucher Sennenhund (n = 8), were analyzed to identify novel, non-CGR genomic contigs using the previously validated pseudo-de novo assembly pipeline. We identified 256,957 novel contigs and paired-end relationships together with BLAT scores provided 126,555 (49%) high-quality contigs with genomic coordinates containing 4.6 Mb of novel sequence absent from the CGR. These contigs close 12,503 known gaps, including 2.4 Mb containing partially missing sequences for 11.5% of Ensembl, 16.4% of RefSeq and 12.2% of canFam3.1+ CGR annotated genes and 1,748 unmapped contigs containing 2,366 novel gene variants. Examples for six disease-associated genes (SCARF2, RD3, COL9A3, FAM161A, RASGRP1 and DLX6) containing gaps or alternate splice variants missing from the CGR are also presented. These findings from non-reference breeds support the need for improvement of the current Boxer-only CGR to avoid missing important biological information. The inclusion of the missing gene sequences into the CGR will facilitate identification of putative disease mutations across diverse breeds and phenotypes.Peer reviewe
Eriyttämisen vaikutus liikunnallisesti lahjakkaiden oppilaiden motivaatioon liikuntatunneilla
Tiivistelmä. Tutkielman tarkoitus oli selvittää, kuinka eriyttäminen vaikuttaa liikunnallisesti lahjakkaan oppilaan motivaatioon liikuntatunneilla ja kuinka eriyttämistä voitaisiin liikuntatunneilla toteuttaa. Työn tavoitteena oli koota yhteen tietoa lahjakkaan oppilaan eriyttämisestä ja erilaisista eriyttämisen keinoista liikuntatunneilla, joita liikuntaa opettavat opettajat voisivat hyödyntää työssään. Työ on toteutettu systemaattisena kirjallisuuskatsauksena. Sen aihe on ajankohtainen, sillä eriyttäminen on ollut aiheena paljon esillä ja uuden perusopetuksen opetussuunnitelman (2016) käyttöönoton myötä yksilöllinen oppiminen on korostunut entisestään.
Lahjakkuustutkijat ovat melko yksimielisiä siitä, että lahjakkuus on joko perittyä tai hankittua. Lahjakkuuden määritelmä on kuitenkin moninainen ja sen ilmenemiseen vaikuttaa useat tekijät. Yksi lahjakkuuden osa-alueista on motorinen lahjakkuus, joka ilmenee usein liikunnallisena lahjakkuutena. Liikunnallisesti lahjakkaiden oppilaiden uskotaan tarvitsevan vertaisiaan vähemmän opetusta, mutta näin ei kuitenkaan ole, vaan he tarvitsevat opetusta, joka ottaa huomioon heidän yksilölliset tarpeensa ja tarjoaa heille riittävän haastavia tehtäviä. Motivaatio on toiminnan ärsyke, joka saa ihmisen tavoittelemaan omaa tai edustamansa yhteisön tavoitetta. Siihen liittyy aina yksilön osallistuminen tavoitteelliseen toimintaan. Eriyttämisellä tarkoitetaan opetuksen muokkaamista, vastaamaan yksilön tarpeita. Näin opettaja pyrkii tarjoamaan jokaiselle oppilaalle parhaat mahdollisuudet oppia. Liikunnanopetusta yksilöidään menetelmillä ja toimenpiteillä, jotka mahdollistavat oppilaan edellytysten mukaisen etenemisen liikuntatunneilla. Tällä tarkoitetaan oppilaiden yksilöllisten erojen tunnistamista, huomioimista ja hyväksymistä opetustilanteissa. Liikunnallisesti lahjakkaiden opetuksessa on kysymys siitä, että opetusta eriytetään vastaamaan myös lahjakkaiden kykyihin ja tarpeisiin.
Liikunnallisesti lahjakkaan oppilaan motivaatioon liittyviä tekijöitä liikuntatunneilla ovat sisäiset, ulkoiset ja sosiaaliset ärsykkeet. Hyvin suunniteltu tunti ja selkeä, johdonmukainen ohjaus mahdollistavat sen, että oppilas kiinnostuu ja innostuu sekä hyödyntää kaiken potentiaalinsa tehtävän suoritukseen. Sisäistä motivaatiota tukeva opetus on sellaista, jossa tehtävät ovat sekä monipuolisia että vaihtelevia ja niissä on mukana jokaisen oppilaan taitotason mukaisia haasteita. Liikunnallisesti lahjakkaan oppilaan opettaminen ja opetuksen suunnittelu vaativat opettajalta enemmän työtä, mutta eriyttäminen liikuntatunnilla tekee oppimisilmapiirin myönteisemmäksi ja motivoi oppilaita toimimaan liikuntatunneilla aktiivisemmin
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