Hagar Ahmed

Bio: Hagar Ahmed is an academic researcher from Banha University. The author has contributed to research in topics: Support vector machine & Breast cancer. The author has an hindex of 3, co-authored 5 publications receiving 36 citations.

New Sequential and Parallel Support Vector Machine with Grey Wolf Optimizer for Breast Cancer Diagnosis

Abstract: Breast cancer is one of the most common types of cancer worldwide. Early detection of cancer increases the probability of recovery. This work has three contributions. The first contribution is improving the performance of support vector machine (SVM) using a recent grey wolf optimizer (GWO) for diagnosis breast cancer with efficient scaling techniques. The second contribution is proposing three efficient scaling techniques against the classical normalization technique. The last contribution is using a parallel technique which applies task distribution to improve the efficiency of GWO. The proposed sequential model is applied on two different datasets, Wisconsin diagnosis breast cancer (WDBC) dataset and Electronic Health Records (EHR). Experimental results of WDBC show that the proposed hybrid GWO-SVM model achieves 98.60% with normalization scaling. Also, using the proposed scaling techniques with the proposed GWO-SVM model gives a fast convergence and achieves accuracy rate by 99.30%. The parallel version of the proposed model achieves a speedup by 3.9 on four CPU cores. On the other hand, Experimental results of EHR show that the proposed hybrid GWO-SVM model achieves 93.26% with normalization scaling against 82.05 for SVM.

From Linear Programming Approach to Metaheuristic Approach: Scaling Techniques

Abstract: The objective of this work is to propose ten efficient scaling techniques for the Wisconsin Diagnosis Breast Cancer (WDBC) dataset using the support vector machine (SVM). These scaling techniques are efficient for the linear programming approach. SVM with proposed scaling techniques was applied on the WDBC dataset. The scaling techniques are, namely, arithmetic mean, de Buchet for three cases , equilibration, geometric mean, IBM MPSX, and Lp-norm for three cases . The experimental results show that the equilibration scaling technique overcomes the benchmark normalization scaling technique used in many commercial solvers. Finally, the experimental results also show the effectiveness of the grid search technique which gets the optimal parameters (C and gamma) for the SVM classifier.

Social Media Sentiment Analysis using Machine Learning and Optimization Techniques

Abstract: Recently, there are emergence and advent of data Inter-personal interaction web sites, micro blogs, wikis, in addition to Web applications and data, e.g. tweets and web-postings express views and opinions on different topics, issues and events in many applications, in addition to, different domains that includes business, economy, politics, sociology, and etc., which are resulted from offering immense opportunities for studying and analyzing human views and sentiment. The objective of sentiment analysis is to classify a speaker's or a writer’s attitude towards various events or topics and arranging data into positive, negative or neutral categories. Sentiment analysis means determining the views of a user from the textual content regarding that topic i.e. how one feels about it. It might be used to classify the text content. Various researchers have used a widespread sort of methods to teach the classifiers for the Twitter dataset with various results. The research uses a hybrid method of using Swarm Intelligence optimization algorithms with classifiers. For each tweet, pre-processing will be done by performing various processes i.e. Tokenization; removal of stop-words and emoticons;

Renewable energy sources in the Egyptian electricity market: A review

Abstract: This review paper presents an appraisal of renewable energy RE options in Egypt. An appraisal review of different REs is presented. The study shows that electric energy produced from REs in Egypt are very poor compared with other energy sources. The utilization of the renewable energies can also be a good opportunity to fight the desertification and dryness in Egypt which is about 60% of Egypt territory. The rapid growth of energy production and consumption is strongly affecting and being affected by the Egyptian economy in many aspects. It is evident that energy will continue to play an important role in the development of Egypt's economy in coming years. The total installed electricity generating capacity had reached around 22025 MW with a generating capacity reached 22605 MW at the end of 2007. Hydropower and coal has no significant potential increase. During the period 1981/82–2004/05 electricity generation has increased by 500% from nearly 22 TWh for the year 1981/1982 to 108.4 TWh in the year 2004/2005 at an average annual growth rate of 6.9%. Consequently, oil and gas consumed by the electricity sector has jumped during the same period from around 3.7 MTOE to nearly 21 MTOE. The planned installed capacity for the year 2011/2012 is 28813 MW and the required fuel (oil and gas) for the electricity sector is estimated to reach about 29 MTOE by the same year. The renewable energy strategy targets to supply 3% of the electricity production from renewable resources by the year 2010. Electrical Coverage Electrical energy has been provided for around 99.3% of Egypt's population, representing a positive sign for the welfare of the Egyptian citizen due to electricity relation to all development components in all walks of life. The article discusses perspectives of wind energy in Egypt with projections to generate ∼ 3.5 GWe by 2022, representing ∼9% of the total installed power at that time (40.2 GW). Total renewables (hydro + wind + solar) are expected to provide ∼7.4 GWe by 2022 representing ∼ 19% of the total installed power. Such a share would reduce dependence on depleting oil and gas resources, and hence improve country's sustainable development.

Wind Energy in Egypt: Economic Feasibility for Cairo

Abstract: Motivated by the rise of the electricity tariffs applied on industrial customer and the frequent electricity cut offs recently experienced in Egypt, this paper assesses the economic feasibility of installing a stand alone wind energy technology by an industrial customer who seeks to reduce his dependency on the national grid. For this purpose, the wind energy potential at the wind regime of Cairo was chosen to be assessed using half an hour wind speed data for a full one-year period (2009). The Weibull parameters of the wind speed distribution function were estimated by employing the maximum likelihood approach. The estimation revealed that Cairo has poor wind resources. Despite the poor resources, the financial analysis has shown that under certain parameters the wind project can prove to be financially viable. Thus harnessing wind energy through stand alone systems can help in meeting the industries electric power needs.

Wind energy characteristics and wind park installation in Shark El-Ouinat, Egypt

Abstract: This work presents the first statistical analysis about the wind characteristics using measured wind speed data for the period of five years by the meteorological station on Shark El-Ouinat City in depth west southern Egyptian desert. The average annual wind speed is obtained as 6.5 m/s over 10 m height. The annual average of Weibull parameters is 2.1 for shape factor k and 7.4 m/s for the scale parameter c. The predominant winds are (360°) with a percentage 47.1% throughout the year. Estimation of wind energy potential per month at 10 m altitude via two various techniques was studied, where Rayleigh distribution is not accurate for fitting it for this location. The wind energy potential from wind that can be arrived is nearly 582 kW/m2 per year at 100 m height that are comparable with and higher than its counterparts at much nations like USA, Brazil, Great Britain, Holland, and Russia. A technical estimation is introduced of electric current production from – a 150 MW wind park- considered at this area, which will which will generate an electrical energy at a rate of 730,791 MWh yearly with capacity factor of 56%, at hub height 100 m. And the expected cost is 1.3 € cent/kWh by using a new simple procedure (methodology) to account for the cost analysis of electricity generated from the wind farms.