Inquiry (E-Journal - Faculty of Business and Administration, International University of Sarajevo)
Not a member yet
209 research outputs found
Sort by
On the Accuracies of Sequence Based Linear B Cell Epitope Predictors
No full textThe accuracy of online tools employed in attempts to predict B-cell epitopes based on sequence are very poor. In order to improve the accuracy of these predictions it is essential to design algorithms to benefit from the features achieved in wet lab in vivo experimental models. To shed some light on accuracy and reliability of these online tools, we set an insilico experiment on five selected online tools using five antigens whose b-cell epitopes are known through wet lab experiments. To evaluate successes of online tools, we defined two measures, accuracy, and reliability. To the findings of this experiment, the most accurate tool is ABCpred with a score of 43.59 %. That is peptides that are predicted as b-epitopes, cover in average 43.59 % of the wet lab listed b-epitopes. The most reliable predictors are BCpred and AAPred with scores of 52.54%, and 52.60% respectively, which means that in average around half of the peptides that are predicted as a b-epitope by these predictors have a chance to be a real b-epitope. Combining several predictors to get better predictors is not an advisable technique. From this experiment it is concluded that the accuracy and reliability of online tools still are far away being satisfactory
Authorship Authentication of Short Messages from Social Networks Machines
Get PDFDataset consists of 17000 tweets collected from Twitter, as 500 tweets for each of 34 authors that meet certain criteria. Raw data is collected by using the software Nvivo. The collected raw data is preprocessed to extract frequencies of 200 features. In the data analysis 128 of features are eliminated since they are rare in tweets. As a progressive presentation, five – fifteen – twenty – twenty five – thirty and thirty four of these authors are selected each time. Since recurrent artificial neural networks are more stable and in general ANNs are more successful distinguishing two classes, for N authors, N×N neural networks are trained for pair wise classification. These experts then organized in N competing teams (CANNT) to aggregate decisions of these NXN experts. Then this procedure is repeated seven times and committees with seven members voted for final decision. By a commonest type voting, the accuracy is boosted around ten percent. Number of authors is seen not so effective on the accuracy of the authentication, and around 80% accuracy is achieved for any number of authors
The Gut-Brain Axis in Foetal-Maternal Relationship
No full textGut-brain axis (GBA) represents a bidirectional communication between the central nervous system (CNS) and gastrointestinal (GI) tract. Microbiota found in GI tract has beneficial relationship with their host and can affect the brain, behavior. Studies performed on animals suggest that any change in the composition of microbiota might cause alternations in behavior. In the same way, changes in behavior such as stress, showed to affect the microbiota. Moreover, the composition of the maternal microbiome in pregnancy is known to adversely influence neonatal and infant health and preterm birth. Mother’s microbiome is inherited from the mother to children
Longest Common Subsequences in Bacteria Taxonomic Classification
No full textIn 1980s, Carl Woese made a ground breaking contribution to microbiology using rRNA-genes for phylogenetic classifications. He used it not only to explore microbial diversity but also as a method for bacterial annotation. Today, rRNA-based analysis remains a central method in microbiology. Many researchers followed this track, using several new generations of Artificial Neural Networks obtained high accuracies using available datasets of their time. By the time, the number of bacteria increased enormously. In this article we used Longest Common Subsequence similarity measure to classify bacterial 16S rRNA gene sequences of 1.820.414 bacteria in SILVA, 3.196.038 bacteria in RDP, and 198.509 bacteria in Greengenes. The last two taxonomy have six taxonomical levels, phylum, class, order, family, genus, and species, while SILVA has two more levels subclass and suborder, but lacks species level. The majority of classifications (98%) were of high accuracy (98%)
Authorship Authentication of Short Messages from Social Networks Using Recurrent Artificial Neural Networks: Massage Batches
No full text500 tweets from Twitterare collectedby using the software Nvivo, fromeach of 34 authorsthat meet certain criteria. Dataset consists of 17000 tweets is preprocessed to extract frequencies of 72 features. Since artificial neural networks are more successful distinguishing two classes, for N authors, N×N neural networks are trained for pair wise classification. These experts then organized as N special competing teams (CANNT) to aggregate decisions of these NXN experts. Then to improve the accuracy of author authentication, a novel technique, batch identification is used and up to100% accuracy is achieved
Determination of Association Rules with Market Basket Analysis: Application in the Retail Sector
Get PDFMarket basket analysis is the process of extracting purchasing trends from
records in company databases, taking into account the products that
customers buy in a single transaction. In this study, a market basket
analysis was conducted on a five-and-a-half year data of a large hardware
company operating in the retail sector, and related product categories
were identified. In determining the association rules, both the Apriori and
FP-Growth algorithms were run separately and their usefulness in such a
set of data was compared. In addition, the data set was divided into Data
Set-1 and Data Set-2 so that the consistency of the rules was discussed by
comparing the correctness of rules extracted from the first data set with
rules derived from the second data set containing consecutive timed data
Authorship Authentication of Short Messages from Social Networks Using Recurrent Artificial Neural Networks
No full textDataset consists of 17000 tweets collected from Twitter, as 500 tweets for each of 34 authors that meet certain criteria. Raw data is collected by using the software Nvivo. The collected raw data is preprocessed to extract frequencies of 200 features. In the data analysis 128 of features are eliminated since they are rare in tweets. As a progressive presentation, five – ten – fifteen – twenty - thirty and thirty four of these 34 authors are selected each time. Since recurrent artificial neural networks are more stable and iterations converge more quickly, in this work this architecture is preferred. In general, ANNs are more successful in distinguishing two classes, therefore for N authors, N×N neural networks are trained for pair wise classification. These N×N experts then organized as N special teams (CANNT) to aggregate decisions of these N×N experts. Number of authors is seen not so effective on the accuracy of the authentication, and around 80% accuracy is achieved for any number of authors
Semi- Markov processes in labor market theory: The case of Switzerland
No full textThe mathematical base of stochastic labor markets is the theory of Markov processes, and the uncertainty is its indivisible part. In this paper, Markov processes are used to calculate the equilibrium position, the time needed to reach it, natural rate of unemployment, transition probabilities and first passage time. While the theories of uncertainty give explanation why workers transit, identify the market anomalies and best fitted Markov model. The findings showed that the semi-Markov labor model better fits Switzerland data. Furthermore, the time needed to reach the equilibrium position is 4.6 years and the right number of employed workers, unemployed and inactive workers maintain the highest rate of uncertainty reduction is 67.16 %, 1.31 % and 31.54 % respectively, where 1.31% is the natural rate of unemployment. What is also important to point out is that the percent of employed workers in Switzerland is expected to decrease from 79.4% to 67.16%, while the percent of inactive workers is projected to increase significantly, from 15.9%to 31.54%. Workers who are expected to transit to an Inactive state in the future and stay there for a longer time are the older works (above 45 years). In other words, the Switzerland labor market is directed toward its “bad” equilibrium. In the end, the demographic structure is considered as one of the main factors for sustainable growth. Therefore, the government is suggested to control the population growth and put into practice new-innovative youth policies,becausethe traditional pro-family policies implemented to encourage bigger families has failed to increase the fertility rates to expected levels
Validation Tools for Predicted Linear B-Epitopes: Surface Accessibility
No full textIdentifying B-cell epitopes plays an important role in vaccine design, immunodiagnostic tests, and antibody production. Therefore, computational tools for reliably predicting B-cell epitopes are highly desirable. In this article the possibility of usage of accessible surface scores of peptides as a validation tool is studied. Janin et al. determined empirical amino acid accessible surface probabilities of twenty amino acids. With these fractional surface probabilities for amino acids, a surface probability (S) at sequence position n can be found using a formula given by Emini et. al. When a peptide is uploaded to the Emini Surface Accessibility Prediction in iedb Analysis Resource, prediction tool separates residues into two groups buried, and surface according to the average of S_ns. To create a criterion to decide whether a given peptide is a linear b-epitope or not, for 344,121 b-epitopes downloaded from iedb database, average buried and exposed probabilities, as well as the ratio ρ of averages for these b-epitopes are computed. The same is done for 111,306 artificially created non epitopes. It is seen that for b-epitopes, the ratio ρ is significantly larger than the ratio ρ for the non epitopes. Therefore if ρ is larger, the peptide is more likely is a b-epitope, and this property can be used as to rank peptides while choosing the most probable linear b-epitope from a long list
Optimal Combination of Three Volatilities for Better Black-Scholes Option Pricing
No full textThe most popular parametric formula (B-S) used in pricing the European-style options is given by Black-Scholes (1973). The prediction power of (B-S) strongly rely on the accuracy of the independent variables: spot price, strike price, time to maturity, risk free interest rate and market volatility. To improve the accuracy, many volatility models are proposed. Also Day and Lewis (1992) introduced the idea of combining implied volatility and EGARCH. In this article an optimal combination of market implied volatility, GARCH(1,1), and GJR(1,1) is made, and the prediction power of B-S is doubled