Fractal Geometry: An Attractive Choice for Miniaturized Planar Microwave Filter Design

Various fractal geometries are characterized by the self-similarity and space-filling properties. The space-filling feature has been successfully applied to design multiband antenna structures for a wide variety of multifunction wireless systems. On another hand, the second feature has proved its validity to produce miniaturized antennas and passive microwave circuits including the band-pass filters (BPF). This chapter demonstrates the design of miniaturized microstrip BPFs that are derived from fractal-based DGS resonators. Many microstrip BPFs based on the Minkowski fractal DGS resonators will be presented together with those based on Moore and Peano fractal geometries. Simulation results, of all of the presented BPFs, show that an extra-size reduction can be obtained as the iteration level becomes higher. Measured and simulated results agree well with each other. A comparison has been conducted with other filters based on Peano and Hilbert fractal geometries. The results reveal that the proposed BPF offers acceptable performance and a significant decrease of higher harmonics

Extracting dualband antenna response from UWB based on current distribution analysis

An entirely new design approach has been employed to create the printed dualband monopole antenna that was the subject of this investigation. The printed monopole antenna construction is the primary component of the suggested design. CPW transmission lines with 50 Ohm impedance and a relative dielectric constant of 4.6 were used to power the antennas, which were housed in thin substrates with thicknesses of 1.6 millimeters (mm). In this study, the antennas discussed were modeled and analyzed by Computer Simulation Technique (CST) simulator. Using fractal structures on the radiating element of a dualband antenna can improve the resonance of the antenna as well as the coupling of the resonating bands that emerge from the resonance

Effect of the initial population construction on the DBMEA algorithm searching for the optimal solution of the traveling salesman problem

There are many factors that affect the performance of the evolutionary and memetic algorithms. One of these factors is the proper selection of the initial population, as it represents a very important criterion contributing to the convergence speed. Selecting a conveniently preprocessed initial population definitely increases the convergence speed and thus accelerates the probability of steering the search towards better regions in the search space, hence, avoiding premature convergence towards a local optimum. In this paper, we propose a new method for generating the initial individual candidate solution called Circle Group Heuristic (CGH) for Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), which is built with aid of a simple Genetic Algorithm (GA). CGH has been tested for several benchmark reference data of the Travelling Salesman Problem (TSP). The practical results show that CGH gives better tours compared with other well-known heuristic tour construction methods

Barramundi (Lates calcarifer) from Iraq: a new record for the Arabian Gulf, with a highlight on it genetic origins and description of two skeletal deformities

The natural distribution of Lates calcarifer (barramundi or Asian sea bass), ranges from western India, around Sri Lanka to the Bay of Bengal, and through the whole of Southeast Asia to Papua New Guinea and northern Australia. It is not known to be native to the Arabian Gulf, although the species has recently been introduced for aquaculture production in Iran. In 2019, 12 adult barramundi were caught from freshwater in the Shatt al-Arab River, its estuary and marine waters bordering Iraq. This is the first wild-capture record of this species for Iraq’s inland waters and the northern Arabian Gulf. The specimens were morphologically described, while genetic structure analyses indicated that the specimens likely originated from Australian and Thailand genetic stocks and thus probably were aquaculture escapees from farmed populations. Among the L. calcarifer collected from the freshwater environment on the Shatt al-Arab River, one specimen exhibited saddleback syndrome, and another showed abnormality in the left operculum. The results are interesting and useful in reminding people to prevent aquaculture escapees. The aim of this study was to morphologically describe the specimens and undertake a genetic analysis to determine the likely provenance of the fish

Ulcerative Colitis Diagnosis Based on Artificial Intelligence System

مرض التهاب القولون التقرحي هو تهيج في القولون الذي يرتبط في كثير من الأحيان مع العدوى ونقص المناعة. يكون جدار القولون للشخص مصاب بالالتهاب دائمًا أكثر سماكة من المعتاد. قد يكون مرض التهاب القولون التقرحي مهدد للحياة ويؤدي إلى الموت إذا لم يتم اكتشافه مبكرًا. الاكتشاف المبكر لهذا المرض مهم للغاية لبدء العلاج المناسب. في هذا البحث، تم تقديم شبكة العصبية الاصطناعية للكشف عن مرض التهاب القولون التقرحي وفقًا لمجموعة البيانات النظرية التي تم إنشاؤها بواسطة المعايير. تم تدريب الشبكة باستخدام خوارزمية Levenberg-Marquardt. أفضل اداء للشبكة كان حيث نسبة الخطأ تساوي 1.9947×10-24   للنظام الذي عدد خلاياه العصبية = 4.Ulcerative colitis (UC) disease is irritation of the colon that is frequently related to infection and immune compromise. The wall of the colon with inflammation is always thicker than normal. UC may be life-threatening and lead to death if not detected early. Early detection of this disease is very important to initiate appropriate treatment. In this paper, the Artificial Neural Network (ANN) applied to detect the UC according to a theoretical dataset generated by the criteria of UC. The Levenberg-Marquardt (LM) algorithm has trained the single hidden layer ANN. The best behaviour is equal to 1.9947×10-24for the system which the number of neurons =4

Waterpipe tobacco use in the United Kingdom: A cross-sectional study among university students and stop smoking practitioners

© 2016 Jawad et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction: Despite cigarette-like adverse health outcomes associated with waterpipe tobacco smoking and increase in its use among youth, it is a much underexplored research area. We aimed to measure the prevalence and patterns of waterpipe tobacco use and evaluate tobacco control policy with respect to waterpipe tobacco, in several universities across the UK. We also aimed to measure stop smoking practitioners' encounter of waterpipe tobacco smoking. Methods: We distributed an online survey to six UK universities, asking detailed questions on waterpipe tobacco. Multivariable logistic regression models, adjusted for age, gender, ethnicity, graduate status, university and socioeconomic status (SES) assessed associations between waterpipe tobacco smoking (single use and dual use with cigarettes) and sociodemographic variables. SES was ascertained by average weekly self-spend on non-essentials. We also descriptively analysed data from a 2012 survey of stop smoking practitioners to assess the proportion of clients that used waterpipe regularly. Results: f 2217 student responses, 66.0%(95% CI 63.9-68.0%) had tried waterpipe tobacco smoking; 14.3%(95% CI 12.8-15.8%) reported past-30 day use, and 8.7% (95% CI 7.6-9.9%) reported at least monthly users. Past-30 day waterpipe-only use was associated with being younger (AOR 0.95, 95% CI 0.91-0.99), male (AOR 1.44, 95% CI 1.08-1.94), higher SES (AOR 1.16, 95% CI 1.06-1.28) and belonging to non-white ethnicities (vs. white, AOR 2.24, 95% CI 1.66-3.04). Compared to less than monthly users, monthly users were significantly more likely to have urges to smoke waterpipe (28.1% vs. 3.1%,

Position paper : A systematic framework for categorising IoT device fingerprinting mechanisms

The popularity of the Internet of Things (IoT) devices makes it increasingly important to be able to fingerprint them, for example in order to detect if there are misbehaving or even malicious IoT devices in one's network. However, there are many challenges faced in the task of fingerprinting IoT devices, mainly due to the huge variety of the devices involved. At the same time, the task can potentially be improved by applying machine learning techniques for better accuracy and efficiency. The aim of this paper is to provide a systematic categorisation of machine learning augmented techniques that can be used for fingerprinting IoT devices. This can serve as a baseline for comparing various IoT fingerprinting mechanisms, so that network administrators can choose one or more mechanisms that are appropriate for monitoring and maintaining their network. We carried out an extensive literature review of existing papers on fingerprinting IoT devices -- paying close attention to those with machine learning features. This is followed by an extraction of important and comparable features among the mechanisms outlined in those papers. As a result, we came up with a key set of terminologies that are relevant both in the fingerprinting context and in the IoT domain. This enabled us to construct a framework called IDWork, which can be used for categorising existing IoT fingerprinting mechanisms in a way that will facilitate a coherent and fair comparison of these mechanisms. We found that the majority of the IoT fingerprinting mechanisms take a passive approach -- mainly through network sniffing -- instead of being intrusive and interactive with the device of interest. Additionally, a significant number of the surveyed mechanisms employ both static and dynamic approaches, in order to benefit from complementary features that can be more robust against certain attacks such as spoofing and replay attacks

Burden of waterpipe smoking and chewing tobacco use among women of reproductive age group using data from the 2012-13 Pakistan Demographic and Health Survey

Background: Despite the general decline in cigarette smoking, use of alternative forms of tobacco has increased particularly in developing countries. Waterpipe (WP) and Chewing Tobacco (CT) are two such alternative forms, finding their way into many populations. However, the burden of these alternative forms of tobacco and their socio demographic determinants are still unclear. We assessed the prevalence of WP and CT use among women of reproductive age group in Pakistan. Methods: Data from the most recent Pakistan Demographic and Health Survey 2012–13 (n = 13,558) was used for this analysis. Information obtained from ever married women, aged between 15 and 49 years were analyzed using two separate data subgroups; exclusive WP smokers (total n = 12,995) and exclusive CT users (total n = 12,771). Univariate and Multivariate logistic regression analyses were conducted and results were reported as crude and adjusted Odds Ratio with 95 % confidence intervals. Results: Prevalence of WP smoking and CT were 4 % and 2 %, respectively. After multivariate adjustments, ever married women who were: older than 35 years (OR; 4.68 95 % CI, 2.62–8.37), were poorest (OR = 4.03, 95 % CI 2.08–7.81), and had no education (OR = 9.19, 95 % CI 5.10–16.54), were more likely to be WP smokers. Similarly, ever married women who were: older than 35 years (OR = 3.19, 95 % CI 1.69–6.00), had no education (OR = 4.94, 95 % CI 2.62–9.33), were poor (OR = 1.64, 95 % CI 1.07–2.48) and had visited health facility in last 12 months (OR = 1.81, 95 % CI 1.22–2.70) were more likely to be CT users as well. Conclusion: Older women with lower socio-economic profile were more likely to use WP and CT. Focused policies aiming towards reducing the burden of alternate forms of tobacco use among women is urgently needed to control the tobacco epidemic in the country

Early diagnosis is associated with improved clinical outcomes in benign esophageal perforation: an individual patient data meta‑analysis

Background Time of diagnosis (TOD) of benign esophageal perforation is regarded as an important risk factor for clinical outcome, although convincing evidence is lacking. The aim of this study is to assess whether time between onset of perforation and diagnosis is associated with clinical outcome in patients with iatrogenic esophageal perforation (IEP) and Boerhaave’s syndrome (BS). Methods We searched MEDLINE, Embase and Cochrane library through June 2018 to identify studies. Authors were invited to share individual patient data and a meta-analysis was performed (PROSPERO: CRD42018093473). Patients were subdivided in early (≤ 24 h) and late (> 24 h) TOD and compared with mixed effects multivariable analysis while adjusting age, gender, location of perforation, initial treatment and center. Primary outcome was overall mortality. Secondary outcomes were length of hospital stay, re-interventions and ICU admission. Results Our meta-analysis included IPD of 25 studies including 576 patients with IEP and 384 with BS. In IEP, early TOD was not associated with overall mortality (8% vs. 13%, OR 2.1, 95% CI 0.8–5.1), but was associated with a 23% decrease in ICU admissions (46% vs. 69%, OR 3.0, 95% CI 1.2–7.2), a 22% decrease in re-interventions (23% vs. 45%, OR 2.8, 95% CI 1.2–6.7) and a 36% decrease in length of hospital stay (14 vs. 22 days, p < 0.001), compared with late TOD. In BS, no associations between TOD and outcomes were found. When combining IEP and BS, early TOD was associated with a 6% decrease in overall mortality (10% vs. 16%, OR 2.1, 95% CI 1.1–3.9), a 19% decrease in re-interventions (26% vs. 45%, OR 1.9, 95% CI 1.1–3.2) and a 35% decrease in mean length of hospital stay (16 vs. 22 days, p = 0.001), compared with late TOD. Conclusions This individual patient data meta-analysis confirms the general opinion that an early (≤ 24 h) compared to a late diagnosis (> 24 h) in benign esophageal perforations, particularly in IEP, is associated with improved clinical outcome.publishedVersio