Inquiry (E-Journal - Faculty of Business and Administration, International University of Sarajevo)
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209 research outputs found
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Taxonomic Classification of Bacteria Using Common Substrings
No full textFor the taxonomic classification of microbes, 16S ribosomal RNA (rRNA) gene sequences are widely used in environmental microbiology as reliable markers. Although the massive sequencing of 16S rRNA gene amplicons encompassing the full length of genes is not easy, because of the limitations of the current sequencing techniques, in databases Greengenes, RDP, and SILVA millions of rRNA gene sequences are uploaded. In this research, first a new similarity measure LCSS, for full length genes is defined. Then it is found that sequences reported for the same bacteria species demonstrate around 53% average sequence similarity in Greengenes and SILVA databases, while average similarity among genes reported for different bacteria species is around 15% only. This is 63%, and 20% respectively at genus level for the three data bases Greengenes, RDP, and SILVA. Hence, species, and genus-specific sequences constitute useful targets for diagnostic assays and other scientific investigations. In the present research, the built in function LongestCommonSubsequence is used repeatedly in computer algebra package MATHEMATICA to create an in silico pipeline for taxonomic classification uploaded new full-length sequences. Conclusions: Our results suggest that LongestCommonSubsequence similarity can be used for taxonomic classification of unknown bacteria through their full 16S ribosomal RNA (rRNA) gene sequences
Zeka - Friendy Chatterbot
Full text linkThe idea of chatbots firstly appeared in the 1960s. But only after more than half a century passed the world became ready for their implementation into the real life, this being a result of the rapid progress in natural language processing, artificial intelligence, and the global presence of text messaging applications. Today, specialized chatbots exist in different domains, thus helping organizations handle large amount of inquiries. Idea of this project was to develop one friendly chatbot with whom you can talk about politics, movies, weather, sport, emotions and similar everyday things. Friendly chatbot named Zeka, is a web-based chatbot developed with the help of Chatterbot library. Chatbot relies on different natural processing and machine learning algorithms altered by its developers to increase its performance
A Survey On Security In Wireless Sensor Network
Full text linkWith the global use of wireless sensor network technology in different fields and for different purposes such as health care monitoring, earth sensing, air pollution monitoring, military operations monitoring or surveillance system monitoring, a problem arises. Problem that could negatively impact previously started activities and observations if not handled in a right way. Authors of this paper discuss various vulnerabilities and security threads in different applications of WSN in the real world, such as intrusion, node capture attack, black hole attack or selective forwarding attack. Potential countermeasures are proposed formatted as protocols or architectures for secure transfer of data between friendly nodes, compromises on security measures with the goal of achieving secure and reliable connection. This paper could be used as a general representation of WSN security issue with which WSN engineers are faced on a daily basis
Movie Recommender System
Full text linkRecommender systems are necessary in current time, since the information available online can be overloading to a user. These systems are used everywhere, starting from the online shops to the websites that are focused
on recommending particular item, such as videos to watch or songs to listen to. Recommender system that predicts the likings of a user based on their previous behavior is very popular when it comes to picking up the movies to watch. This paper talks more about the movie recommender systems, and explains the way that different types of recommendations can be used in order to test datasets and provide good recommendations for variety of users
Hypervariable Regions in 16S rRNA Genes for the Taxonomic Classification
Full text link16S ribosomal RNA (rRNA) gene sequences are reliable markers for the taxonomic classification of microbes and widely used in environmental microbiology. Production of 16S rRNA gene amplicons in large amounts, encompassing the full length of genes is not yet feasible, because of the limitations of the current sequencing techniques. They are mostly in short reads of length less than 300 base pairs. Hence, the selection of the most efficient hypervariable regions for phylogenetic analysis and taxonomic classification is a current research area. It is found that nine hypervariable regions (V1–V9), resides in bacterial 16S ribosomal RNA (rRNA) genes. Family, genus, and species-specific sequences within a given hypervariable region constitute useful targets for diagnostic assays and other scientific investigations. In this study systematic studies that compare the relative advantage of hypervariable regions grouped as V1–V2–V3, V4–V5–V6, and V7–V8–V9 for specific diagnostic goals are done. In the present research, the built in function Longest–Common–Subsequence in computer algebra package MATHEMATICA is used to create an in silico pipeline to evaluate the taxonomic classification sensitivity of the hypervariable regions compared with the corresponding full-length sequences. Conclusions: Our results suggest that V4–V5–V6 region might be an optimal sub-region for the design of universal primers with superior phylogenetic resolution for bacterial phyla
A Review on Image Enhancement Techniques
No full textImage Enhancement is one of the most important and complex techniques in image processing technology. The main aim of image enhancement is to improve the visual appearance on an image and to offer a better representation of the image for Computer Vision Algorithms. In this paper,we is covered a few application fields of image enhancement with various images like grayscale, color, infrared and even with videos. The main objective of this paper is to highlight the drawbacks of the state of the art image enhancement techniques
Analytic Hierarchy Process (AHP) to Solve Complex Decision Problems
No full textIn this thesis covers two different examples which we solved with Analytic Hierarchy Process (AHP).The Analytic Hierarchy Process was explained with details in this study. People encounter problems which are difficult to solve and understand. Decision making becomes more complex with apply common procedures without knowing any decision making application. AHP is the one of the application to use in decision analysis problem which is helping to change non-numerical judgments to convert in the system with numerical values for decision making process. It allows us to find out which alternative is the optimum as a result in the problem. In this study, 2 problems were solved with AHP. On the first example, it is considered for making decision to buy new phone. There are suggested 3 criteria and 4 alternatives
On the Accuracy of the 16S-rRNA Gene Conserved Regions
No full textThe study of microbial communities through sequencing the 16S rRNA gene by the use of high throughput sequencing technology has emerged as a significant improvement for the discipline. However, the short size of these sequences is a limiting factor for the taxonomic classification of bacteria and archaea. These short reads are amplified from DNA, using primers. Although several researchers claim that they succeeded to create the best universal primers, the reality is that no primer has been demonstrated to be truly universal. This suggests that conserved regions of the 16S rRNA gene is not conserved enough. The aim of this study is to evaluate the conservation degree of the conserved regions separating the hypervariable regions of the 16S rRNA genes. Data contained in Greengenes, SILVA, and RDP databases are used for the study. Primers reported as matches of each conserved region were assembled to form fifteen contigs by Martinez-Porchas et al. (2017). Under the information of the degenerate bases in primes these contıgs are multiplied to cover all possibilities of degenerate bases. In Greengenes database there are 198.510 non redundant 16S rRNA genes are reported. This number is 1.488.662 for, SILVA, and 1.350.270 for RDP. To analyze the level of conservation of a contig, one gene is selected from one database, then using the longest common subsequences, for each of these 15 contigs, the longest common subsequences are found between a contig, and a gene. Then the length of longest common subsequence is divided by the length of the contig to get the percentage of conservation of this contig in that gene. This is done for each contig, in the entire databases. Averages revealed that the segments of contigs are not as conserved as expected, 72% in Greengenes, 71% in SILVA, and 57% in RDP. It is concluded that conserved regions of the 16S rRNA genes exhibit considerable variation that has to be considered when using these conserved regions as bases for primer production
Assessment of Accuracies of Protein 3-Dimensional Prediction Software
No full textProtein 3-dimensional structure prediction is determination of the 3-dimensional structure of a protein from its amino acid sequence by using protein structure prediction software. By understanding protein’s 3-dimensional structure, we should be able to figure out the function of the said protein. We already have several protein prediction software, but the purpose of this study is to determine how accurate they are, and if the results presented are true and to what extent. To determine how accurate protein 3-dimensional structure prediction software are, we compared x-ray crystallography determined protein structures to software predicted 3-dimensonal protein structures. All of the software used showed good accuracy, and according to our results, “i-Tasser” software was the most accurate, closely followed by RaptorX
Artificial Neural Networks in Bacteria Taxonomic Classification
No full textIn 1980s, the face of the microbiology dramatically changed with the rRNA-based phylogenetic classifications, by Carl Woese. He delineated the three main branches of life. He used the technique 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 they obtained high accuracies using available datasets of their time. Recently the number of known bacteria increased enormously. In this article we used ANN's to annotate bacterial 16S rRNA gene sequences from five selected phylums in Greengenes database taxonomy: Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, and Chloroflexi. 93% average accuracy is obtained in classif-ications. When we used the bundle testing technique, the average accuracy easily raised to 100%