Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM deep learning model. By applying Pearson's correlation, we found that the sentiment of the day (d) had a positive effect on the future Bitcoin returns on the next day (d+1). The prediction accuracy of the linear regression model for the next day's revenue was 78%.
The leaves and stems of the local Purslane plant ( Portulaca oleracea oleracea L. ) were used to preapare the extract of two types ( wet and dried extractions) the extracts were prepared by weighting of 60grams of the wet and the dried plant individually, then boiled in 500ml of distal water. Finally the volume was completed to1 liter, then we used these extracts to prepare of 8 types of the culture media contained basic, selective and enrichment media for growing a group of pathogenic bacteria. 8 types of bacteria were used for this purpose: Escherichia coli, Pseudomonas flouresence, Staphylococcus aureus , Staphylococcus epidermidis, Bacillus subtilis , Klebsiella pneumoniae , Proteus mirabilis and Proteus vulgaris. The stastica
... Show MoreIn this article four samples of HgBa2Ca2Cu2.4Ag0.6O8+δ were prepared and irradiated with different doses of gamma radiation 6, 8 and 10 Mrad. The effects of gamma irradiation on structure of HgBa2Ca2Cu2.4Ag0.6O8+δ samples were characterized using X-ray diffraction. It was concluded that there effect on structure by gamma irradiation. Scherrer, crystallization, and Williamson equations were applied based on the X-ray diffraction diagram and for all gamma doses, to calculate crystal size, strain, and degree of crystallinity. I
... Show MoreMultiple myeloma is hematological disease produces many complications in the bone, kidney, neural and other complications. The study aims to measure serum biomolecules like fetuin-A and resistin and determined the possibility to use these biomarkers as disease predictor. blood samples were isolated from 58 patients and 24 sex and age-matched control, serum then isolated, and proper ELISA kit then used to a determined level of B2 microglobulin, resistin, and fetuin-A. The result demonstrated significant increase in B2 microglobulin, fetuin-A and resistin in patients compare to control (1.3470.714 vs. 0.9130.253), p = 0.000, (14.00310.352 vs. 9.2594.264), p= 0.005, (1.9673.595 vs. 0.6040.622), p = 0.009, respectively. &
... Show MoreThis study was aimed to investigate the genetic variability of 26 rice genotypes and evaluation at two locations in Sulaimani governorate, Gaba and Chawtan which were completely different in their environmental condition during the season of 2019. The performances of the genotypes were analyzed at both locations as well as the average of both. Simple coefficients of correlation were used to assess the grain yield components and their relationships. Path analysis was used to determine the direct and indirect effects of such components on grain yield plant-1. The genotypes were grouped based on the agro-morphological features using cluster analysis. Almost all of the traits at both locat
... Show MoreThis research is mostly concerned of exploration analysis of a random sample of data from Al-sadder hospital. We examine duration of hospital stay (DHS) and investigate any significant difference in duration between sex, age groups, occupation, patients’ condition at admission, and patients’ condition at discharge
Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreThis study includes the preparation of the ferrite nanoparticles CuxCe0.3-XNi0.7Fe2O4 (where: x = 0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3) using the sol-gel (auto combustion) method, and citric acid was used as a fuel for combustion. The results of the tests conducted by X-ray diffraction (XRD), emitting-field scanning electron microscopy (FE-SEM), energy-dispersive X-ray analyzer (EDX), and Vibration Sample Magnetic Device (VSM) showed that the compound has a face-centered cubic structure, and the lattice constant is increased with increasing Cu ion. On the other hand, the compound has apparent porosity and spherical particles, and t
... Show MoreAmong the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the
... Show MoreBackground: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.
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