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[Vol. 06, No. 05] May 2020

Paper Title :: Application of genetic algorithm to solve BAO problem
Author Name :: Nika Topuria || Omar Kikvidze
Country :: Georgia
Page Number :: 01-05
Beam angle optimization (BAO) is acomplex, multi-objective, non-convex problem with many local minima. Most modern approaches use deterministic or hybrid techniques to solve above-mentioned problem, however problem, however avoiding premature convergence and local minima entrapment is still quite a big problem for most algorithms. In this paper we demonstrate results of our PHD thesis, in which we apply Genetic Algorithm based approach to BAO problem with high success in comparison to clinically used Varian BAO system. MatRad open-source system was used as a software platform to implement our Bao module in MATLAB programming language.
Keywords: Algorithm, BAO, Genetic, MatRad, Optimization
[1] D. Djajaputra, Q. Wu, Y. Wu, and R. Mohan, “Algorithm and performance of a clinical IMRT beam-angle optimization system,” Phys. Med. Biol., vol. 48, no. 19, pp. 3191–3212, 2003.
[2] H. Rocha, J. Dias, T. Ventura, B. Ferreira, and M. do C. Lopes, “A derivative-free multistart framework for an automated noncoplanar beam angle optimization in IMRT: A derivative-free multistart framework for an automated BAO,” Med. Phys., vol. 43, no. 10, pp. 5514–5526, 2016.
[3] M. Ehrgott, A. Holder, and J. Reese, “Beam selection in radiotherapy design,” Linear Algebra Appl., vol. 428, no. 5–6, pp. 1272–1312, 2008.
[4] Y. Li, J. Yao, and D. Yao, “Automatic beam angle selection in IMRT planning using genetic algorithm,” Phys. Med. Biol., vol. 49, no. 10, pp. 1915–1932, 2004.
[5] N. Topuria and O. Kikvidze, “Application of Genetic Algorithm in Common Optimization Problems,” Int. Ann. Sci., vol. 8, no. 1, pp. 17–21, 2019.


Paper Title :: Digital color image encryption-decryption using segmentation and reordering
Author Name :: Dr. Majed Omar Dwairi || Prof. Ziad Alqadi || Dr. Mohammad S. Khrisat || Dr. Amjad Hindi || Dr. Saleh A. Khawatreh
Country :: Jordan
Page Number :: 06-12
Digital color image is very famous and important data type; it is used in many important vital applications such as banking systems, protection and security systems, so image protection is required. In this research paper we will introduce a simplified method of color image encryption-decryption; the method will be based on image segmentation and reordering using two private keys, it will be tested and implemented using various color images. The issues of security, efficiency and accuracy will be discussed; the obtained experimental results will be analyzed in order to raise some enhancement factors.
Keywords: Color image, encryption, decryption, PSNR, secret key, secret range, encryption time, efficiency measures, speedup, and throughput, MSE, PSNR.
[1]. Majed O Al-Dwairi, Ziad A Alqadi, Amjad A Abujazar, Rushdi Abu Zneit, Optimized true-color image processing, World Applied Sciences Journal, vol. 8, issue 10, pp. 1175-1182, 2010.
[2]. Jamil Al Azzeh, Hussein Alhatamleh, Ziad A Alqadi, Mohammad Khalil Abuzalata, Creating a Color Map to be used to Convert a Gray Image to Color Image, International Journal of Computer Applications, vol. 153, issue 2, pp. 31-34, 2016.
[3]. AlQaisi Aws, AlTarawneh Mokhled, A Alqadi Ziad, A Sharadqah Ahmad, Analysis of Color Image Features Extraction using Texture Methods, TELKOMNIKA, vol. 17, issue 3, 2018.
[4]. Mohammed Ashraf Al Zudool, Saleh Khawatreh, Ziad A. Alqadi, Efficient Methods used to Extract Color Image Features, IJCSMC, vol. 6, issue 12, pp. 7-14, 2017.
[5]. Akram A. Moustafa and Ziad A. Alqadi, Reconstructed Color Image Segmentation, Proceedings of the World Congress on Engineering and Computer Science, WCECS 2009, vol. II, 2009.


Paper Title :: Implementation of a system of improvements in the management of changes in healthcare facilities - barrier analysis
Author Name :: Joanna Jasińska
Country :: Poland
Page Number :: 13-22
The aim of the scientific article is to identify factors and barriers in the system of supporting change management in healthcare organizations. Based on the results of research conducted in April 2019, the research method is surveys and interviews with healthcare professionals, it was possible to identify the most serious deficiencies in implementing changes. Research has shown a number of barriers that block the innovative activity of employees and managers. The article also presents the manager's activities of the analyzed organizations, which aims to mobilize staff to achieve a higher level of functioning of the healthcare facility.
Keywords: change management, continuous improvement, pro-innovative attitudes.
[1]. Cieśliński B.W. (2017), Doskonalenie procesowej orientacji przedsiębiorstw: model platformy treningu procesowego, Wydawnictwo Uniwersytetu Ekonomicznego, Wrocław.
[2]. Johannessen J.A., Olsen B., Lumpkin G.T. (2017), Innovation as newness: what is new, how new, and new to whom?, „European Journal of Innovation Management”, vol. 4, no.1, s. 20-31.
[3]. Jřrgensen F.,TimenesLaugen B., Boer H. (2017), Human resource management for continuous improvement,„Creativity and Innovation Management”, vol. 16, no. 4.
[4]. KleinknechtA.,Mohnen P. (red.) (2015), Innovation and Firm Performance: Econometric Explorations of Survey Data, Palgrave, Basingstoke.
[5]. Kotarbiński T., (1998)Traktat o dobrej robocie, Ossolineum, Wrocław.


Paper Title :: Customer Feedback Analysis in Afan Oromo Texts
Author Name :: Eshetu Gusare Desisa || Dr. Dida Midekso
Country :: Ethiopia
Page Number :: 23-31
When trying to make a good decision, we must weigh the positivity and negativity of human feedback and consider all the alternatives. As a result, human feedback is the primary part of decision making and the thought process of selecting a logical choice from the available persuasion.During decision making processes most of us get help from others and it is a natural fact that good decision can be taken on the basis of opinions of others.Accordingly, before the development of today‟s technologies, all the above mentioned facts have been practiced by asking families, neighbors, elders, friends and experts manually for decision making. Nowadays, opinions are found on the Internet everywhere and anytime.Despite its availability, it is unstructured and making information access challenging. To overcome this challenges, in our work we have proposed a feedback analysis model for AfanOromo texts. Feedback analysis is the process of computationally analyzing and categorizing human feedback or opinions expressed in a piece of texts especially to determine whether the writer's or Customer‟s attitude towards a particular topic, product, service and etc. is positive, strongly positive, weakly positive, negative, strongly negative, weakly negative or neutral. Consequently, this study proposes feedback analysis model for AfanOromo texts by using manually constructed rules and subjectivity lexicon of the language. The proposed model comprises of Nine main key components. These are: text preprocessing, morphological analysis, grammar checking, sentiment terms detection, ambiguity detection, polarity propagation, feedback‟s polarity weight calculation, feedback‟s polarity classification and the developed subjectivity lexicon of AfanOromo language. The developed prototype detects subjectivity words of a feedback from the developed lexicon and assigns an initial polarity weight for each sensed sentiment terms in order to determine the polarity classification of the feedback in AfanOromo texts. The developed lexicon of AfanOromo sentiment terms is used for recognizing and assigning initial polarity values for each of sentiment terms detected from entered feedback. The prototype has been developed for verifying the proposed model and the algorithms designed. As a result, experiments have been done on three different data sets and the achieved result with these test data is very encouraging.
Keywords: Subjectivity, Analysis, Lexicon, Feedback, Sentiment, Intensifier, Overstatement, Understatement
[1]. Khairullah Khan, Baharum B.Baharudin, Aurangzeb Khan and Fazal-e-Malik, “Mining Opinion from Text Documents”, A Survey of 3rd IEEE International Conference on Digital Ecosystems and Technology, Petronas, Malaysia, July 2009.
[2]. Bing Liu, “Sentiment Analysis and Opinion Mining”, Unpublished Thesis, Department of Computer Science, University of Illinois at Chicago, 2012.
[3]. Ravendra Ratan and Singh Jandail, “A Proposed Novel Approach for Sentiment Analysis and Opinion Mining”, International Journal of UbiComp, Vol.5, No.1/2, 2014, pp. 1-2.
[4]. David Alfred Ostrowski, “Sentiment Mining within Social Media for Topic Identification”, IEEE Fourth International Conference on Semantic Computing, 2010.
[5]. Samaneh Moghaddam and Martin Ester, “ILDA: Interdependent LDA Model for Learning Latent Aspects and their Ratings from Online Product Reviews”, in Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, Beijing, China, July 2011.



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