Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Making (MCDM) methods, the Analytic Hierarchy Process (AHP) is preferred for handling complicated decision-making challenges using several criteria. The Consistency Ratio (CR) scores were used to examine pair-wise comparisons to evaluate the AHP. This study used two judgment scales to get the most consistent judgment. Firstly, the Saaty judgment scale (SS), then the Generalized Balanced Scale (GBS). It investigated whether two different AHP judgment scales would affect decision-making. The main criteria for prioritizing pre-processing techniques in sentiment analysis are Punctuation, Spelling, Number, and Context. These four criteria also contain sub-criteria. GBS pair-wise comparisons are closer to the CR value than SS, reducing the alternatives’ weight ratios. This paper explains how AHP aids logical decision-making. Prioritizing pre-processing techniques with AHP can be a paradigm for other sentiment analysis stages. In short, this paper adds another contribution to the Big Data Analytics domain.
The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also
... Show MoreFaujasite type NaY zeolite catalyst was prepared from locally available kaolin, then the prepared NaY zeolite have been modified by exchanging of sodium ion with ammonium to produce NH4Y zeolite. NH4Y zeolite was converted to HY zeolite by ion exchanging with oxalic acid. Zinc and nickel promoters have been added to the prepared HY zeolite catalyst, and the effect of these promoters on the catalytic activity of the prepared HY catalyst was studied in fluid catalytic cracking process using light gas oil as a feedstock. The experimental results show that the promoted catalyst gives higher gas oil conversion and gasoline yield than HY zeolite catalyst at the same reaction temperature and WHSV. It was also found that the promoted catalyst gi
... Show MoreMost statistical research generally relies on the study of the behaviour of different phenomena during specific time periods and the use of the results of these studies in the development of appropriate recommendations and decision-making and for the purpose of statistical inference on the parameters of the statistical distribution of life times in The technical staff of most of the manufacturers in the research units of these companies deals with censored data, the main objective of the study of survival is the need to provide information that is the basis for decision making and must clarify the problem and then the goals and limitations of this study and that It may have different possibilities to perform the
... Show MoreIn 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 MoreData Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need
... Show MoreAmoxicillin is commercially available in the form of capsules and tablets containing 250mg or 500mg for oral administration. It is also available in the form of suspension containing "25mg/ml†. Amoxicillin is presently used as the most common antibiotics .Ten healthy Human volunteers were characterized respected to their pharmacokinetic and bioavailability of two formulations of Amoxicillin from two sources of industrial companies after a single dose administration was given orally. A procedure is described for determination the concentration levels of Amoxicillin in human plasma of healthy volunteers using high performance liquid chromatography (HPLC) with reversed-phase isocratic column at low wave length of UV-visib
... Show MoreWhen embankment is constructed on very soft soil, special construction methods are adopted. One of the techniques is a piled embankment. Piled (stone columns) embankments provide an economic and effective solution to the problem of constructing embankments over soft soils. This method can reduce settlements, construction time and cost. Stone columns provide an effective improvement method for soft soils under light structures such as rail or road embankments. The present work investigates the behavior of the embankment models resting on soft soil reinforced with stone columns. Model tests were performed with different spacing distances between stone columns and two lengths to diameter ratios of the stone columns, in addition to different
... Show MoreThis study deals with the estimation of critical load of unidirectional polymer matrix composite plates by using experimental and finite element techniques at different fiber angles and fiber volume fraction of the composite plate.
Buckling analysis illustrated that the critical load decreases in nonlinear relationship with the increase of the fiber angle and that it increases with the increase of the fiber volume fraction.
The results show that the maximum value of the critical load is (629.54 N/m) at (q = 0°) and (Vf = 40 %) for the finite element method, while the minimum val
... Show MoreThis article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.
This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta
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