A novel fractal design scheme has been introduced in this paper to generate microstrip bandpass filter designs with miniaturized sizes for wireless applications. The presented fractal scheme is based on Minkowski-like prefractal geometry. The space-filling property and self-similarity of this fractal geometry has found to produce reduced size symmetrical structures corresponding to the successive iteration levels. The resulting filter designs are with sizes suitable for use in modern wireless communication systems. The performance of each of the generated bandpass filter structures up to the 2nd iteration has been analyzed using a method of moments (MoM) based software IE3D, which is widely adopted in microwave research and industry. Results show that these filters possess good transmission and return loss characteristics, besides the miniaturized sizes meeting the design specifications of most of wireless communication systems.
KE Sharquie, SM Al-Tammimy, S Al-Mashhadani, RK Hayani, AA Al-Nuaimy, Dermatology online journal, 2006 - Cited by 34
Although rare, coarctation of aorta is a treatable cause of hypertension, transcatheter dilatation by balloon with or without stent are a well-known treatment strategy
This study aims to assess the effect of adding twisted fins in a triple-tube heat exchanger used for latent heat storage compared with using straight fins and no fins. In the proposed heat exchanger, phase change material (PCM) is placed between the middle annulus while hot water is passed in the inner tube and outer annulus in a counter-current direction, as a superior method to melt the PCM and store the thermal energy. The behavior of the system was assessed regarding the liquid fraction and temperature distributions as well as charging time and energy storage rate. The results indicate the advantages of adding twisted fins compared with those of using straight fins. The effect of several twisted fins was also studied to discover
... Show Morethe research was exposed to a study the importance of the role of the supportive entities in providing the useful information to the tax administration and their ability to extend the level of the tax base of taxpayers, through the improvement of the tax payers determination and their tax settle for the purpose of increasing the tax revenue, and shed light on the legal evidence through which these entities become officially assigned to perform a supplementary task to the General Committee for Taxes GCT, to help it to perform its task efficiently, and to study the reasons of the weak cooperation of the supportive entities and their reluctance to provide useful information which leads to limiting the tax base.
The research data hav
... Show MoreThe present study aimed to identify the therapeutic evaluation of chitosan extracted from the fungus cushroom and pure chitosan on glucose and lipid profile in the blood of 35 male rabbits with hyperlipidemia induced experimentally by cholesterol. The tests included estimation of glucose levels, total cholesterol, triglycerides, high-density lipoproteins, low-density lipoproteins, and very low-density lipoproteins. hyperlipidemia was induced in the male rabbits used in the study which was administered orally with cholesterol 150mg/kg body weight for a week. rabbits were divided into seven groups: control, cholesterol, pure chitosan, mushroom chitosan, cholesterol and pure chitosan, cholesterol and mushroom chitosan and cholestero
... Show MoreResearchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
... Show MoreIn networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show More