There are many tools and S/W systems to generate finite state automata, FSA, due to its importance in modeling and simulation and its wide variety of applications. However, no appropriate tool that can generate finite state automata, FSA, for DNA motif template due to the huge size of the motif template. In addition to the optional paths in the motif structure which are represented by the gap. These reasons lead to the unavailability of the specifications of the automata to be generated. This absence of specifications makes the generating process very difficult. This paper presents a novel algorithm to construct FSAs for DNA motif templates. This research is the first research presents the problem of generating FSAs for DNA motif templates and offers novel algorithm to accomplish this. It is tested using many simple and compound motif templates of different sizes and various numbers of gaps that have unlimited ranges of intervals. The motifs sizes are up to 2M Bases. The motif templates include up to 2000 gaps and the interval of a gap is [1,100] up to [1, 1000000]. All of these cases were processed successfully.
Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with mis
In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f
... Show MoreVerbs in German and Arabic are of two types: active and passive. Passive voice is a grammatical voice construction that is found in many languages. Out of grammatical perspective, each main verb has a form in the active and one in the passive known as a "genus verbi" (type of verb). In passive voice, both in German and in Arabic, the focus is on the action itself or on the result of the action; often the perpetrator is not mentioned. In German, to conjugate verbs in the passive voice, you must know the forms of werden (to become). German uses werden + the past participle and states it at the end of a sentence. In Arabic,
... Show MoreAbstract: This study aims to investigate the effects of solvents of various polarities on the electronic absorption and fluorescence spectra of RhB and Rh6G. The singlet‐state excited dipole moments (me) and ground state dipole moments (mg) were estimated from the equations of Bakshiev -Kawski and Chamma‐ Viallet using the variation of Stokes shift along with the solvent’s dielectric constant (e) and refractive indexes (n). The observed singlet‐state excited dipole moments were found to be larger than the ground‐state ones. Moreover, the obtained fluorescence quantum yield values were influenced by the environment of the fluorescing molecule. Consequently, the concentration of the dye solution, excited singlet state absorption and
... Show MoreThis study was aimed to establish a database of autosomal Short Tandem Repeat (aSTR) DNA allele frequencies for an Iraqi population living in Baghdad city as a reference, therefore, a total of 456 unrelated individuals were analyzed at 15 STR DNA markers (D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317, D7S820, TH01, TPOX, CSF1PO, D19S433, D2S1338, D16S539) included in the Kit from Applied Biosystems. The obtained results revealed that the Combined Matching Probability (CMP) was estimated at 1 in 3.3287 × 10-18, and the Combined Discrimination Power (CDP) was greater than 0.98600987, which is comparable to values obtained with the many other allele frequency databases used in forensic investigations. It can be con
... Show MoreAn experimental study is carried out on the effect of vortex generators (Circular and square) on the flow and heat transfer at variable locations at (X = 0.5, 1.5, 2.5 cm) ahead of a heat exchanger with Reynolds number ranging from 62000< Re < 125000 and heat flux from 3000 ≤ q ≤ 8000 W/m2 .
In the experimental investigation, an apparatus is set up to measure the velocity and temperatures around the heat exchanger.
The results show that there is an effect for using vortex generators on heat transfer. Also, heat transfer depends on the shape and location. The circular is found t
... Show MoreIn this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show MoreIn this work, an estimation of the key rate of measurement-device-independent quantum key distribution (MDI-QKD) protocol in free space was performed. The examined free space links included satellite-earth downlink, uplink and intersatellite link. Various attenuation effects were considered such as diffraction, atmosphere, turbulence and the efficiency of the detection system. Two cases were tested: asymptotic case with infinite number of decoy states and one-decoy state case. The estimated key rate showed the possibility of applying MDI-QKD in earth-satellite and intersatellite links, offering longer single link distance to be covered.
The nuclear level density parameter in non Equi-Spacing Model (NON-ESM), Equi-Spacing Model (ESM) and the Backshifted Energy Dependent Fermi Gas model (BSEDFG) was determined for 106 nuclei; the results are tabulated and compared with the experimental works. It was found that there are no recognizable differences between our results and the experimental -values. The calculated level density parameters have been used in computing the state density as a function of the excitation energies for 58Fe and 246Cm nuclei. The results are in a good agreement with the experimental results from earlier published work.