Inquiry (E-Journal - Faculty of Business and Administration, International University of Sarajevo)
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Better Features Sets for Authorship Attribution of Short Messages
Get PDFAuthorship authentication analysis can help to display information about the writers of messages by analyzing the writing styles. Previous researches in the authorship authentication were showed that generally people have their unique stylistic discriminators and characteristics, just like their fingerprints or signature. In this concept, researchers are developing different analysis features and techniques and have gained remarkable results in the authorship identification research field.
Authorship authentication of online messages became an outstanding research topic in the last decades because of internet usage growth. One of the problems of authorship authentication analysis regarding online sources is short messages usage. Author identification techniques are started to be applied to short and informal texts in last decade and get very significant results.
Authorship authentication is one of the security concerns in social network and in this research we will study how to authenticate a user by the writing style in a short text posted on Twitter. The effects of different feature sets and sample sizes are evaluated in the research
A Literature Survey on Reverse Logistics of End of Life Vehicles
Get PDFToday, recycling of used products and materials has become an increasingly important sector. Mankind, who uses the natural resources unconsciously, has found ways to improve recycling techniques when they realized that resources are becoming increasingly depleted. In the automotive sector, which is one of the largest sectors in the world, natural resources are being used to a great extent. According to the statistics, in 2009, approximately 9 million end-of-life vehicles (ELV) in Europe were withdrawn from traffic. Undoubtedly, this figure shows the necessity and importance of designing reverse logistics network optimized for ELVs. This research aims to determine the gaps in the literature by examining the studies made from the past to the present day in the field of reverse logistic network design for vehicles that have completed their life cycle. In this article, the studies in the fieldare analyzed based on objective functions, decision variables, constraint handling metod, optimization methods used. Considered studies in this work are clustered using a special artificial neural network tool, Self-Organizing Maps (SOM), and the frequencies of the characteristics are shown in the study. This study, which includes a review of the literature and a clustering of studies, aims to guidethe researchers working on the design of rreverse logistics networks for ELVs
The Analysis of Transformational Leadership Behaviors and Their Relation with Organizational Commitment
Get PDFThis study aims to analyze transformational leadership behaviors and its relation with organizational commitment in high school managers and teachers in Istanbul, Turkey. The effect of transformational leadership on organizational commitment was investigated in the study. In this context, some research questions were created and a literature review was performed. Some specific hypothesis statement was developed, tested, and finalized. Quantitative research design was applied in this research with cross-sectional time frame. Convenience sampling method was used in the study. Data was obtained from 135 participants. The population of the study comprised teachers, principals, study program coordinators, managers, administrators and other staff from nine public high schools in Istanbul, Turkey. A structured self-completed quantitative research survey was conducted in this study which was distributed to the participants of the study and collected in two months. The main research instrument for data collection in this study was a survey with five descriptive and 11 inferential statistics questions. In this research, quantitative survey was the main instrument for primary data collection which was designed in a “5” and “7” - point Likert’s scale. The data was analyzed with SPSS (Statistical Package for the Social Sciences) version 20. The research questions and a hypothesis were developed for the study which were tested with Chi square, correlations, and t-test. Null hypothesis (H0) was rejected (
Accuracy of Identical Subsequences Based Protein Secondary Structure Prediction
No full textChou, and Fasman developed the first empirical prediction method to predict secondary structure of proteins from their amino acid sequences. Subsequently, a more sophisticated GOR method has been developed. Although it became very popular among biologists, their accuracy was only slightly better than random. A significant improvement in prediction accuracy >70% has been achieved by ‘second generation’ methods such as PHD, SAM-T98, and PSIPRED, which utilized information concerning sequence conservation. Only recently F. B. Akcesme developed a local similarity based method to obtain an accuracy >90%in secondary structure prediction of any new protein. In this article we examined the possibility of sequence similarity based secondary structure prediction of proteins. To deal with this issue, all proteins of PDB dataset are searched for identical subsequences in the other larger proteins of PDB dataset. It is seen that around 17% of proteins in the PDB dataset have identical subsequences in other larger proteins of PDB dataset. When the secondary structures of proteins are assigned as the corresponding secondary structures of identical parts in other larger proteins, the average prediction accuracy is found to be 90.39 %. Therefore, we concluded that an unknown protein has a chance of 17 % to have an identical subsequence in a larger protein in Protein Data Bank (PDB), and there is a possibility that its secondary structure be predicted with around 90% accuracy with this method
Forecasting Conditional Variance of S&P100 Returns Using Feedforward and Recurrent Neural Networks
No full textIt is shown that time series about financial market variables are highly nonlinearly dependent on time. Fluctuations or volatility of returns on assets is one of them. Portfolio managers, option traders and market makers are all interested in volatility forecasting in order to get higher profits and less risky positions. The nonlinear dependence on time is very complex and parametric approaches, and linear models fail. Therefore as nonparametric tools artificial neural networks (ANNs) are candidates to deal with the volatility and/or return forecasting problems. On the other hand, based on the fact that volatility is time varying and that periods of high volatility tend to cluster, the most popular models in modeling volatility are GARCH type models because they can account excess kurtosis and asymmetric effects of financial time series. A standard GARCH(1,1) model usually indicates high persistence in the conditional variance, which may originate from structural changes. Hence it is natural that artificial neural networks (ANN) will be constructed to capture the nonlinear relationship between past return innovations and conditional variance which may be missed by linear regression models. First a usual feedforward, back propagation network is used. The structure of the return data makes FFANN difficult to converge. To overcome this difficulty a neural network with appropriate recurrent connections in the context of nonlinear ARMA models are used. These are the Jordan neural networks (JNN). Then Elman recurrent networks (ENN) and a mixture of the two (EJNN) are also used. The data set consists of returns of the S&P100 index daily closing prices obtained from the S&P100 website. The results indicate that the selected JNN(1,1,1) model has superior performances compared to the standard GARCH(1,1) model. The contribution of this paper can be seen in determining the appropriate NN that is comparable to the standard GARCH(1,1) model and its application in forecasting conditional variance of stock returns. Moreover, from the econometric perspective, NN models are used as a semi-parametric method that combines flexibility of nonparametric methods and the interpretability of parameters of parametric methods
On the Accuracy of Sequence Similarity Based Protein 3D Prediction
No full textIn an article (Akcesme, and Can 2015), authors examined the relation between primary and secondary structure mismatches of the substrings of length seventeen residues from two different proteins. They have shown that the mismatches in the corresponding secondary structure sequence substrings of the same length mostly lag behind primary mismatches. In the PhD dissertation thesis (Akcesme 2016) author examined the possibility of secondary structure prediction by the use of smaller conserved segments and created a software AVISENNA that outperforms PSIPRED and all other available secondary structure prediction tools. In another article (Akcesme, et. al. 2017), the issue of how far secondary structure of proteins can be predicted based on hosts (larger proteins that contain the query protein as a subchain) of this protein in the set of solved structures currently deposited in PDB. It is seen that around 17% of proteins have hosts in PDB, and secondary structures of them can be predicted with a mean accuracy of 90.39 %. This accuracy of the host based secondary structure prediction set also an upper bound for the homology based tertiary structure predictions. In this article the impact of the mentioned inaccuracy on the homology based 3D structure predictions by the three predictors I-Tasser, Phyre2, and SwissModel are studied. Inaccuracies in predicted tertiary structures are seen in the visual comparison of the 3D structures of query proteins and their predicted 3D images by the three 3D predictors, and their counterparts in host proteins
Continuous-time Markov chain in labor market theory: The case of United Kingdom
No full textIn this paper, the claim that the sojourn times in the UK labor market follow a continuous-time Markov model is investigated. It means that they are independent random variables and mainly they control how rapidly transits take place. In this case sojourn times in a state before they transit another state are exponentially distributed with an appropriate parameter λ_i.
The labor market model presented in this paper is based on Markov process techniques and have been developed in Wolfram Mathematica 9. The model allows us to calculate the long-run proportion of workers transitions, first-passage time and the transition state probabilities. These parameters are then used to detect labour market failures and accordingly propose policies and procedures that Government can use to build a more efficient labour market and increase employability
Digital Image Techniques for the Comet-FISH Assay in the Search for DNA Damage and Repair
No full textStudies worldwide have demonstrated that the Comet-FISH assay can detect DNA damage and repair in a number of genes, gene regions and loci. Any gene could be detected if a suitable probe is available in theory. Assay’s relative speed and sensitivity make it a very handy laboratory technique for studying the cellular response to damage. It has also the advantage of being able to study specific genes and gene regions of interest, particularly those associated with disease. Its speed and sensitivity also makes it versatile for use in a clinical setting whereby data can be quickly supplied from patient cell samples. The test helps to get information about the development of treatment. This is proved to be particularly beneficial in cancer management, where increasing emphasis is being placed on personalized medicine. Until recently, no research group has yet reported the successful use of a reliable software package for accurately counting hybridization signals from comet slides. They prefer counting signals manually. Manual work is both time consuming and laborious, and also brings in user subjectivity. This study is an attempt in computerization of the process. In a case study, the comet image is processed by the help of digital image handling techniques, and parameters that will help to decide about the DNA damage are derived
Four-Color Coloring of a Partial Map of Europe
Get PDFThe four-color theorem states that any map in a plane can be colored using four-colors in such a way that regions sharing a common boundary other than a single point do not share the same color. In this article we attempt to color a partial map of Europe with four color using Artificial Intelligence techniques, defining it as a Constraint Satisfaction Problem (CSP). The algorithm created was succeeded to find all four solutions of the problem
A Promising Similarity Based Secondary Structure Prediction Method
No full textAssigning secondary structure to amino acid sequences is challenging task due to complexity of protein folding. Protein structures differ enormously. Here, we analyze the mapping between amino acid sequence and secondary structure in a set of 80,592 non-redundant protein chains from the PDB (Protein Data Bank). To identify local conserved regions, we restricted our attention only to the components of these structures of window sizes from 7, to 45. In this article, we examined the issue of how far secondary structure of proteins can be predicted based on the similar segments of solved structures currently deposited in PDB. It is seen that for almost all proteins, secondary structures can be predicted with a mean accuracy of 92%. This accuracy is the highest in the literature