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An efficient binary salp swarm algorithm with crossover scheme for feature selection problems
Full text linkSearching for the (near) optimal subset of features is a challenging problem in the process of Feature Selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superior performance in solving this problem. This motivated our attempts to test the performance of the newly proposed Salp Swarm Algorithm (SSA) in this area. As such, two new wrapper FS approaches that use SSA as the search strategy are proposed. In the first approach, eight transfer functions are employed to convert the continuous version of SSA to binary. In the second approach, the crossover operator is used in addition to the transfer functions to replace the average operator and enhance the exploratory behavior of the algorithm. The proposed approaches are benchmarked on 22 well-known UCI datasets and the results are compared with 5 FS methods: Binary Grey Wolf Optimizer (BGWO), Binary Gravitational Search Algorithms (BGSA), Binary Bat Algorithm (BBA), Binary Particle Swarm Optimization (BPSO), and Genetic Algorithm (GA). The paper also considers an extensive study of the parameter setting for the proposed technique. From the results, it is observed that the proposed approach significantly outperforms others on around 90% of the datasets
The investigation of cybercrime and proving it in Palestine : a comparative study
No full textمقال نشر في مجلة دراسات : علوم الشريعة و القانون ، مج. 45، ع. 4، ملحق 2، 2018الملخص
التحقيق في الجرائم الإلكترونية وكيفية ضبط الأدلة الرقمية وجمعها من الموضوعات المستجدة في فلسطين وغيرها من دول العالم. كما أن طبيعة الأدلة الرقمية وكيفية التعامل معها من قبل جهات التحقيق تعتبر من الموضوعات ذات الأهمية القانونية والعملية. ويقوم بالتحقيق في الجرائم الالكترونية نيابة متخصصة وفق إجراءات وقواعد إثبات خاصة، يساعدها في ذلك ضابطة قضائية متخصصة بالجرائم الالكترونية، على عكس الجرائم التقليدية التي تختص بالتحقيق فيها النيابة العامة تساعدها الضابطة القضائية ذات الاختصاص العام وفقاً لقواعد التحقيق والإثبات التقليدية.
ويعترض عمل النيابة العامة والضابطة القضائية العديد من الصعوبات، من أهمها القصور التشريعي وضعف التخصص لدى القائمين على التحقيق وجمع أدلة هذا النوع من الجرائم. إن تعزيز وتقوية التحقيق في الجرائم الإلكترونية يقوم على وضع إجراءات إدارية لقسم التحقيق لضمان السيطرة الفعّالة على قضايا الجرائم الإلكترونية، إضافةً إلى وضع مبادئ توجيهية للأدلة الإلكترونية الجنائية وصولاً إلى تحقيق ناجح وفعّال للجرائم الإلكترونية
Caesarean section in Palestine using the Robson Ten Group Classification System: a population-based birth cohort study
No full textObjective To analyse the current situation of caesarean section in Palestine using the Robson Ten Group Classification System (TGCS). Design A population-based birth cohort study.
Setting Obstetrical departments in three governmental hospitals in Gaza. Participants All women (18 908) who gave birth between1 January 2016 and 30 April 2017.
Methods The contributions of each group to the study population and to the overall rate of caesarean section were calculated, as well as the rate of caesarean section in each TGCS group. Differences in proportions between study hospitals were assessed by χ2 test. Main outcome measures The main outcome was the contributions of each group to the overall caesarean
section rate. Results The overall rate of caesarean section was 22.9% (4337 of 18 908), ranging from 20.6% in hospital 1 to 24.6% in hospital 3. The largest contributors to the overall caesarean section rate were multiparous women with single cephalic fullterm pregnancy who had undergone at least one caesarean section (group 5, 42.6%), women with multiple pregnancies (group 8, 11.6%) and those with single cephalic preterm labour (group 10, 8.1%).
Statistically significant differences in caesarean section rates between the study hospitals were
observed in group 1 (nulliparous women with single cephalic full-term pregnancy and spontaneous labour), group 4 (multiparous with single cephalic full-term pregnancy with induced labour or prelabour caesarean section), group 5 (multiparous with single cephalic full-term pregnancy with previous caesarean section) and in group 7 (multiparous with breech
presentation). Conclusion Women in groups 5, 8 and 10 were the largest contributors to the overall caesarean section rate in the study hospitals. Efforts to reduce the differences in obstetrical care between hospitals need to be directed towards increasing the proportion of vaginal births after caesarean section and by reducing primary caesarean section in multiple pregnancies and preterm labourNorwegian Research Counci
Environmental Situation in the Palestinian Context: Current Water, Wastewater and Solid Waste Management
No full textpresentatio
Agricultural technologies and carbon emissions: evidence from Jordanian economy
No full textTheoretically, agriculture can be the victim and the cause of climate change. Using annual data for the period of 1970–2014, this study examines the interaction between agriculture technology factors and the environment in terms of carbon emissions in
Jordan. The results provide evidence for unidirectional causality running from machinery, subsidies, and other transfers, rural access to an improved water source and fertilizers to carbon emissions. The results also reveal the existence of bidirectional causality between the real income and carbon emissions. The variance error decompositions highlight the importance of subsidies and machinery in explaining carbon emissions. They also show that fertilizers, the crop and livestock production, the land under
cereal production, the water access, the agricultural value added, and the real income have an increasing effect on carbon emissions over the forecast period. These results are important so that policy-makers can build up strategies and take in
considerations the indicators in order to reduce carbon emissions in Jordan
State of emergency
No full textArabic Abstract:تنطلق الدراسة من أهمية موضوعها الذي يعالج حالة الطوارئ باعتبارها إحدى الحالات الواردة ضمن نظرية الظروف الاستثنائية، التي تُشرع لمواجهة خطر معين حال وجسيم تعاصره الدولة، بموجبها يحق للسلطة التنفيذية تجميد الأحكام الدستورية والتشريعية العادية بشكل مؤقت بما يخدم المصلحة العليا لمواجهة هذا الظرف الطارئ.
تناولت الدراسة بعض المواضيع المرتبطة بحالة الطوارئ ومن ضمنها القيود القانونية لإعلانها وأثر تطبيقها على حقوق الأفراد وحرياتهم. وتوصلت الدراسة إلى عدد من النتائج أهمها: يجب الالتزام بالعديد من القيود الموضوعية والشكلية لإعلان حالة الطوارئ، كأن يتم إعلانها من قبل أشخاص محددين بنص الدستور أو القانون المنظم لها، ولمدة زمنية محددة. هذا ويقع العبء الأكبر في الرقابة على هذه الأعمال على المحكمة الإدارية، أما المحكمة الدستورية تبحث فقط مدى انسجام الإجراءات المتخذة خلال حالة الطوارئ من الجهات المختصة بذلك مع ما ورد من تقييدات ضمن نصوص الدستور
Supervised Training of Spiking Neural Network by Adapting the E-MWO Algorithm for Pattern Classification
No full textSpiking neural networks (SNN) are more realistic and powerful than the preceding generations of the neural networks (e.g. multi-layer perceptron networks). The SNN can be applied for simulating the brain and its functions, as well as it is able to be employed for different applications such as pattern classification. Different methods have been proposed for supervised training of SNN, however, most of them were validated based on using the classical XOR problem, and they consume long training time if other problems are considered. This paper proposes a new supervised training method for SNN by adapting the Enhanced-Mussels Wandering Optimization algorithm. In addition, a SNN model for pattern classification is proposed. The proposed work is used for pattern classification of real-world problems
Feature selection using binary particle swarm optimization with time varying inertia weight strategies
No full textIn this paper, a feature selection approach that based on Binary Particle Swarm Optimization (PSO) with time varying inertia weight
strategies is proposed. Feature Selection is an important preprocessing technique that aims to enhance the learning algorithm (e.g.,
classification) by improving its performance or reducing the processing time or both of them. Searching for the best feature set is
a challenging problem in feature selection process, metaheuristics
algorithms have proved a good performance in finding the (near)
optimal solution for this problem. PSO algorithm is considered a
primary Swarm Intelligence technique that showed a good performance in solving different optimization problems. A key component
that highly affect the performance of PSO is the updating strategy
of the inertia weight that controls the balance between exploration
and exploitation. This paper studies the effect of different time varying inertia weight updating strategies on the performance of BPSO
in tackling feature selection problem. To assess the performance of
the proposed approach, 18 standard UCI datasets were used. The
proposed approach is compared with well regarded metaheuristics based feature selection approaches, and the results proved the
superiority of the proposed approach
