Data Analytics and Techniques: A Review

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide improvements for many applications. In addition, critical challenges and research issues were provided based on published paper limitations to help researchers distinguish between various analytics techniques to develop highly consistent, logical, and information-rich analyses based on valuable features. Furthermore, the findings of this paper may be used to identify the best methods in each sector used in these publications, assist future researchers in their studies for more systematic and comprehensive analysis and identify areas for developing a unique or hybrid technique for data analysis

A Comparative Study for String Metrics and the Feasibility of Joining them as Combined Text Similarity Measures

This paper aims to introduce an optimized Damerau–Levenshtein and dice-coefficients using enumeration operations (ODADNEN) for providing fast string similarity measure with maintaining the results accuracy; searching to find specific words within a large text is a hard job which takes a lot of time and efforts. The string similarity measure plays a critical role in many searching problems. In this paper, different experiments were conducted to handle some spelling mistakes. An enhanced algorithm for string similarity assessment was proposed. This algorithm is a combined set of well-known algorithms with some improvements (e.g. the dice-coefficient was modified to deal with numbers instead of characters using certain conditions). These algorithms were adopted after conducting on a number of experimental tests to check its suitability. The ODADNN algorithm was tested using real data; its performance was compared with the original similarity measure. The results indicated that the most convincing measure is the proposed hybrid measure, which uses the Damerau–Levenshtein and dicedistance based on n-gram of each word to handle; also, it requires less processing time in comparison with the standard algorithms. Furthermore, it provides efficient results to assess the similarity between two words without the need to restrict the word length

Inhibitory activity of Iranian plant extracts on growth and biofilm formation by Pseudomonas aeruginosa

Aims: Pseudomonas aeruginosa is a drug resistance opportunistic bacterium. Biofilm formation is key factor for survivalof P. aeruginosa in various environments. Polysaccharides may be involved in biofilm formation. The purpose of thisstudy was to evaluate antimicrobial and anti-biofilm activities of seven plant extracts with known alpha-glucosidaseinhibitory activities on different strains of P. aeruginosa.Methodology and results: Plants were extracted with methanol by the maceration method. Antimicrobial activities weredetermined by agar dilution and by growth yield as measured by OD560nm of the Luria Bertani broth (LB) culture with orwithout extracts. In agar dilution method, extracts of Quercus infectoria inhibited the growth of all, while Myrtuscommunis extract inhibited the growth of 3 out of 8 bacterial strains with minimum inhibitory concentration (MIC) of 1000μg/mL. All extracts significantly (p≤0.003) reduced growth rate of the bacteria in comparison with the control withoutextracts in LB broth at sub-MIC concentrations (500 μg/mL). All plant extracts significantly (p≤0.003) reduced biofilmformation compared to the controls. Glycyrrhiza glabra and Q. infectoria had the highest anti-biofilm activities. Nocorrelation between the alpha-glucosidase inhibitory activity with growth or the intensity of biofilm formation was found.Conclusion, significance and impact of study: Extracts of Q. infectoria and M. communis had the most antimicrobial,while Q. infectoria and G. glabra had the highest anti-biofilm activities. All plant extracts had anti-biofilm activities withmarginal effect on growth, suggesting that the mechanisms of these activities are unrelated to static or cidal effects.Further work to understand the relation between antimicrobial and biofilm formation is needed for development of newmeans to fight the infectious caused by this bacterium in future

The Relationship between Surface Soil Moisture with Real Evaporation and Potential Evaporation in Iraq

The aim of this research is to determine the relationship between surface Soil Moisture (SSM) of both Real Evaporation (E) and surface Potential Evaporation (SPE) for thirty years during the period of (1985-2014) for the eight stations (Sulaymaniya, Mosul, Tikrit, Baghdad, Rutba, Kut, Nukhayib, Basrah) in Iraq, from (NOAA) and taking advantage of some statistics such as the Simple Linear Regression (SLR) and the Spearman Rho test. Calculated the monthly average for Soil Moisture, Real Evaporation and Potential Evaporation, and found to increase the values of SPE in hot months and decreased in cold months while opposite to SM There was a strong inverse relationship between them, where the correlation coefficient was in Sulaymaniya -0.91, in Mosul -0.89, in the Rutba -0.92, in Tikrit -0.89, in Baghdad -0.89, in Nukhayib -0.89, in Kut -0.87, and in Basrah -0.83, and there is a high correlation in stations (Basrah, Kut, Nukhayib, and Rutba), while there is an average correlation in the stations (Baghdad and Tikrit), and there is low correlation in the stations (Sulaymaniya, Mosul), we also note an inverse correlation between RE and PE, where there is a low correlation in Sulaymaniya and medium correlation in the Mosul and Rutba stations, and there is a high correlation in the stations (Tikrit, Baghdad, Nukhayib, Kut, and Basrah)

Improving the Resistance of Self Compacting Concrete exposed to Elevated Temperatures by Using Steel Fiber

Elevated high temperatures due to fire represents one of the most severe risks to buildings and structures, which negatively affects on the engineering properties for constituent members of these buildings. The study aims to investigate the role of  steel fiber to improve of  properties of self compacting concrete (SCC) at elevated temperature (25, 200, 400 and 600°C) with two different exposure durations of (0.5 and 1.5 hours). Specimens were exposed to temperature and tested at age (7, 28 and 90 days) .The slump flow and T500mm, L-box, and Sieve segregation resistance were conducted to investigate the fresh properties of SCC. Whereas the properties of hardened concrete were inspected using compression test, splitting tensile test, and flexural , as well as modulus of elasticity tests. The results indicate that Elevated temperatures and increasing of exposure duration had  passively influenced on hardened properties of both plain and reinforced SCC, hardened properties of two type of SCC decreased with increased temperatures and increasing of exposure duration. Also the results indicate that steel fiber used in self-compacting concrete reduced the amount of deterioration of properties of Self compacting fiber-reinforced concrete (SCFRC) at high temperature. The percentage change ( improvement ) for mixes with steel fiber (0.5 and 1%) with respect to mixes without steel fiber , where compressive strength ranged between (0.3-20.9%) at 200 o C, (-3.1-31.3%) at 400 o C and (-3.9-31.5%) at 600 o C. Also the best percentages of increase were in splitting tensile strength and flexural strength , the percentages of increase in splitting tensile ranged between (27-94%) at 200 o C, (39-121%) at 400 o C and (38-109%) at 600 o C. and the percentage of increase in flexural strength ranged between (68-146%)  at 200 o C, (75-122%) at 400 o C and (45-109%) at 600 o C. Also the percentage of increase in static modulus of elasticity ranged between (4.3-15.5%) at 200 o C and (6.1-18.3%) at 400 o C for mixes with steel fiber (0.5 and 1%) with respect to reference mixture. It had also emerged the spalling phenomenon at parts of cylinders and prisms specimens  at exposed to high temperatures (400 oC), at  the duration of exposure was 1.5 hours, and the temperature (600 oC) at duration of exposure 0.5 and 1.5 hours. Keywords: Self compacting concrete , elevated  temperature , Steel Fiber , Compressive strength, Splitting tensile , Flexural strength , modulus of elasticity, spalling phenomenon

Leser-Trélat Sign without Internal Malignancy

Leser-Trélat sign is characterized by the abrupt appearance of multiple seborrheic keratoses in association with underlying malignant disease. A case of Leser-Trélat sign in a 66-year-old healthy woman is presented. Evaluation and follow-up for the development of malignancy over a 2-year period failed to reveal any evidence of malignancy. To date, almost all cases of Leser-Trélat sign have been reported in association with an underlying malignancy. It is less known that Leser-Trélat sign can also occur in healthy individuals in the absence of internal malignancy

A HYBRID DEEP LEARNING APPROACH FOR SENTIMENT ANALYSIS IN PRODUCT REVIEWS

Product reviews play a crucial role in providing valuable insights to consumers and producers. Analyzing the vast amount of data generated around a product, such as posts, comments, and views, can be challenging for business intelligence purposes. Sentiment analysis of this content helps both consumers and producers gain a better understanding of the market status, enabling them to make informed decisions. In this study, we propose a novel hybrid approach based on deep neural networks (DNNs) for sentiment analysis in product reviews, focusing on the classification of sentiments expressed. Our approach utilizes the recursive neural network (RNN) algorithm for sentiment classification. To address the imbalanced distribution of positive and negative samples in social network data, we employ a resampling technique that balances the dataset by increasing samples from the minority class and decreasing samples from the majority class. We evaluate our approach using Amazon data, comprising four product categories: clothing, cars, luxury goods, and household appliances. Experimental results demonstrate that our proposed approach performs well in sentiment analysis for product reviews, particularly in the context of digital marketing. Furthermore, the attention-based RNN algorithm outperforms the baseline RNN by approximately 5%. Notably, the study reveals consumer sentiment variations across different products, particularly in relation to appearance and price aspects

Some Immunological and Hematological Parameters among Refugees in Kawergosk Camp – Erbil Governorate

The study included 258 Syrian refugees of different ages and sex and another 60 volunteers as control group (C.G). These refugees were in Kawergosk camp in Erbil Governorate. Blood was collected from each individual for the estimation of white blood cell (WBC), eosinophil, iron, hemoglobin (Hb), and immunoglobulin E (IgE) levels. Mean serum levels of IgE among male and female refugees showed highly significant increasing when compared to C.G. Most of the refugees had normal iron levels, where iron concentrations were more than 65 mg/dl among 67 males and more than 50 mg/dl among 104 females and 48 children, while some had iron deficiency in which the majority were female (9 males, 24 females, and 6 children had iron deficiency). In addition, Hb concentrations were normal among 65 males (more than 13.0 g/dl), 89 females (more than 11.0 g/dl), and 48 children (more than 12.0 g/dl). However, anemia was found among 8 men, 42 women, and 6 children. It was revealed that there was a highly significant rising in eosinophils in male and female refugees in comparison to C.G. WBC count is non-significantly slightly increased in both male’s and female’s refugees when compared to C.G