Among 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

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

In this study, the relationship between the bare soil temperature with respect to its salinity is presented, the bare soil feature is considered only by eliminating all other land features by classifying the site location by using the support vector machine algorithm, in the same time the salinity index that calculated from the spectral response from the satellite bands is calibrated using empirical salinity value calculated from field soil samples. A 2D probability density function is used to analyze the relationship between the temperature rising from the minimum temperature (from the sunrise time) due to the solar radiation duration tell the time of the satellite capturing the scene image and the calibrated salinity index is presented. T

This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

Background This study aimed to evaluate the efficacy of once-daily liraglutide as an add-on to oral antidiabetics (OADs) on glycemic control and body weight in obese patients with inadequately controlled type 2 diabetes (T2D). Methods A total of 27 obese T2D patients who received 7 months (0.6 mg/day for the first month, 1.2 mg/day for 3 months, and 1.8 mg/day for 3 months) of liraglutide treatment as an add-on to OADs were included. Data on body weight (kg), fasting plasma glucose (FPG, mg/dL), postprandial glucose (PPG, mg/dL), and HbA1c (%), were recorded. Results Liraglutide doses of 1.2 mg/day and 1.8 mg/day were associated with significant decreases in body weight (by 8.0% and 11.9%, respectively, p < 0.01 for each) and HbA1c (by 20.0

The present study is an attempt to throw light on the nature of the US policy regarding the Middle East region as portrayed by AI-Sabah, Al-Mashriq and Tariq Al-Shaab papers over a period of three months from 1st of July to 30th of September 2013.

In writing this study, a number of goals have been set by the researcher. These goals may include but in no way limited to the nature of the US image as carried by the above three papers, the nature of the topics tackled by them and the nature of the Arab countries which received more and extensive coverage than others.

A qualitative research approach is proposed for the study. This approach has allowed the researcher to arrive at definite answers for the possible questions rais