Modified global flower pollination algorithm and its application for optimization problems

Flower Pollination Algorithm (FPA) has increasingly attracted researchers’ attention in the computational intelligence field. This is due to its simplicity and efficiency in searching for global optimality of many optimization problems. However, there is a possibility to enhance its search performance further. This paper aspires to develop a new FPA variant that aims to improve the convergence rate and solution quality, which will be called modified global FPA (mgFPA). The mgFPA is designed to better utilize features of existing solutions through extracting its characteristics, and direct the exploration process towards specific search areas. Several continuous optimization problems were used to investigate the positive impact of the proposed algorithm. The eligibility of mgFPA was also validated on real optimization problems, where it trains artificial neural networks to perform pattern classification

Projected Statewide Traffic Forecast Parameters using Artificial Neural Networks

Design-hour volume (DHV) and directional DHV (DDHV) are important traffic forecast parameters for both planning and operational studies. They are used for roads and intersection design and operational analysis. Estimating these two parameters requires a record of hourly volumes for every hour in a year. Therefore, permanent traffic counters are usually used to keep a record of those hourly volumes. The use of permanent counters faces several challenges because of adjacent construction activities and hardware or communication failure. These challenges result in the missing part of the collected data. Moreover, estimating DHV and DDHV based on short-term traffic counts is often needed. In this research, an artificial intelligence approach is used to estimate DHV and DDHV for roadways with different functional classifications. An artificial neural network model, which utilises historical records of annual average daily traffic along with other road characteristics, such as number of lanes and functional classification, is developed. Results show that the model was able to achieve a highly accurate and reliable DHV and DDHV estimates

Natural treatment systems for reclaimed water use and bioresource recovery: A Palestinian experience

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Triple-shape coexistence and superdeformation in Pb isotopes

An article published in Journal : Acta Physica Polonica Series B, vol. 49, no. 9, pp. 1653-1681, October 2018Received the Journal in March 14, 2018; accepted May 6, 2018Triple-shape coexistence and superdeformation in Pb isotopes with neu- tron numbers N = 96 –138 is studied. The constrained calculations are performed within the Relativistic Hartree–Bogoliubov (RHB) model using DD-ME2, DD-PC1, and NL3* force parameters, and pairing interaction separable in momentum space. Triple-shape coexistence (spherical, prolate and oblate) manifests themselves in a clear manner in 184 − 190 Pb nuclei with axial RHB calculations. Triaxial RHB calculations further confirm the find- ings. Superdeformed minimum is observed for 188 − 220 Pb isotopes, and the corresponding excitation energy, deformation and depth of well are compa- rable within different force parameters used. The behaviour with neutron number of the superdeformed excitation energy, two-neutron separation energy in the ground state and superdeformed minimum, and its differ- ential are fairly reproducing the trend of the available experimental data. The present numerical results are compared with Macro–microscopic Fi- nite Range Droplet Model (FRDM) and Hartree–Fock–Bogoliubov (HFB) model based on the interaction Gogny-D1S force. Overall, a fairly satis- factory agreement is found within the different force parameters and the calculated and experimental result

Asynchronous accelerating multi-leader salp chains for feature selection

Feature selection is an imperative preprocessing step that can positively affect the performance of data mining techniques. Searching for the optimal feature subset amongst an unabridged dataset is a challenging problem, especially for large-scale datasets. In this research, a binary Salp Swarm Algorithm (SSA) with asynchronous updating rules and a new leadership structure is proposed. To set the best leadership structure, several extensive experiments are performed to determine the most effective number of leaders in the social organization of the artificial salp chain. Inspired from the behaviour of a termite colony (TC) in dividing the termites into four types, the salp chain is then divided into several sub-chains, where the salps in each sub-chain can follow a different strategy to adaptively update their locations. Three different updating strategies are employed in this paper. The proposed algorithm is tested and validated on 20 well-known datasets from the UCI repository. The results and comparisons verify that utilizing half of the salps as leaders of the chain can significantly improve the performance of SSA in terms of accuracy metric. Furthermore, dynamically tuning the single parameter of algorithm enable it to more effectively explore the search space in dealing with different feature selection datasets

Neimark-Sacker Bifurcation of a Fourth Order Difference Equation

In this article, we study stability and bifurcation of a fourth order rational difference equation. We give condition for local stability, and we show that the equation undergoes a Neimark-Sacker bifurcation. Moreover, we consider the direction of the Neimark-Sacker bifurcation. Finally, we numerically validate our analytical results

Temperature analysis as an indicator of climate change in the Central Palestinian Mountains

Global warming is an anthropogenic-related phenomenon that is affecting the available natural resources, especially water in arid and semiarid regions. Such phenomenon can affect countries with very limited water resources, such as in the Middle East in general and in Palestine specifically. The effect of multiple temporal scales (annual, seasonal, and monthly levels) on temperature trends as an indication of climate change in the Central Palestinian Mountains of the Middle East was studied. Analysis of the available thermal data from 1970 to 2011 was done to test whether the Central Palestinian Mountains is subjected to warming or not. The results showed an increase in temperature during different months of the year, but such increase was statistically significant for the months from June to December and ranging from 0.6 °C in September to 1.2 °C in August. Besides, summer and autumn were the seasons that temperature increased significantly, where such increase equals to 1.1 and 1.8 °C, respectively. Finally, the mean annual temperature was also subjected to a significant increase by about 0.8 °C during the study period, especially after 1990. The results warrant proper policies and suitable adaptation measures by the concerned authorities in the study area so as to release the negative consequences and preserve the limited water resources.Fund from the Vice President for Academic Affairs at Birzeit Universit

Decisions of the Palestinian constitutional judiciary

يختص القضاء الدستوري في فلسطين بالرقابة على دستورية القوانين، و كذلك اختصاصات أخرى كتفسير نصوص الدستور. و لأهمية هذا القضاء في تحقيق دولة القانون القائمة على مبدأ سمو الدستور، نستعرض في هذه الورقة القرارات الصادرة عن القضاء الدستوري الفلسطيني، تلك الصادرة عن المحكمة العليا بصفتها الدستورية، و كذلك المحكمة الدستورية العليا، في قسمين؛ الأول يتضمن ملخصات حول هذه القرارات –على شكل بطاقات تعريفية- و تشمل رقم القرار؛ تاريخ القرار؛ مكان انعقاد المحكمة؛ طبيعة الدعوى؛ آلية الاتصال بالدعوى؛ الجهة الطاعنة؛ الجهة المطعون ضدها؛ الموضوع؛ و ملخص منطوق القرار. أما القسم الثاني منه يحتوي –على شكل ملاحق- النص الكامل للقرارات