Information centric networking (ICN) is the next generation of internet architecture with its ability to provide in-network caching that make users retrieve their data efficiently regardless of their location. In ICN, security is applied to data itself rather than communication channels or devices. In-network caches are vulnerable to many types of attacks, such as cache poisoning attacks, cache privacy attacks, and cache pollution attacks (CPA). An attacker floods non-popular content to the network and makes the caches evict popular ones. As a result, the cache hit ratio for legitimate users will suffer from a performance degradation and an increase in the content’s retrieval latency. In this paper, a popularity variation me

    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin

A simple, accurate, precise, rapid, economical and a high sensitive spectrophotometric method has been developed for the determination of tadalafil in pharmaceutical preparations and industrial wastewater samples, which shows a maximum absorbance at 204 nm in 1:1 ethanol-water. Beer's law was obeyed in the range of 1-7?g/ mL ,with molar absorptivity and Sandell ? s sensitivity of 0.783x105l/mol.cm and 4.97 ng/cm2respectively, relative standard deviation of the method was less than 1.7%, and accuracy (average recovery %) was 100 ± 0. 13. The limits of detection and quantitation are 0.18 and 0.54 µg .ml-1, respectively. The method was successfully applied to the determination of tadalafil in some pharmaceutical formulations

The current study was carried out to investigate the correlation of gene expressions of ADA1 and ADA2 genes with the development of autoimmune thyroid disease (AITD) in a sample of Iraqi females. One hundred patients with AITD and 80 controls were included. Quantitative real time polymerase chain reaction (qRT–PCR) was utilized for investigation of ADA1 and ADA2 gene expression among patients and controls. The correlation of age and body mass index (BMI) with AITD occurrence comparing with controls was studied. Based on the results of this study, there is high expression level of ADA1 and ADA2 genes in patients compared with healthy controls; also, the gene expression fold (2-ΔΔCT) of ADA1 and ADA2 among AITD patients was recorded and a

MRSA is one of the major pathogens in hospitals and the community, which have the ability to produce biofilm as a virulence factor, the impact of chalcone on biofilm formation, the synergism effect of chalcone and antibiotic in both in vitro and in vivo experiments, the gene expression of virulence genes (srtA, fnbA, fnbB) before and after treatment of it on MRSA biofilm cells in vitro, all these were the prime aims of this study. Chalcone at MBIC (20 μg/ml), significantly reduced the biofilm formation to 21.45% and at sub MBIC (15 μg/ml) to 36.58 %. While, Chalcone at MIC(5 μg/ml) reduced MRSA planktonic cells to 49.61%. Susceptibility of MRSA isolates against eight antibiotics showed that all isolates were sensitive to vancomycin and n

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

Diabetic retinopathy is an eye disease, because of pressure in eye nerve fiber. It is a major cause of blindness in middle as well as older age groups; therefore it is essential to diagnose it earlier. Some of the challenges are in the diagnosis of the disease is detection edges of the image, may be some important edges are missed outcome the noise around the corners.
Wherefore, in order to reduce these effects in this paper, we proposed a new technique for edge detection using traditional operators in combination with fuzzy logic based on fuzzy inference system. The results show that the proposed fuzzy edge detection technique better than of traditional techniques, where vascular are markedly detected over the original.

The Normalization Difference Vegetation Index (NDVI), for many years, was widely used in remote sensing for the detection of vegetation land cover. This index uses red channel radiances (i.e., 0.66 μm reflectance) and near-IR channel (i.e., 0.86 μm reflectance). In the heavy chlorophyll absorption area, the red channel is located, while in the high reflectance plateau of vegetation canopies, the Near-IR channel is situated. Senses of channels (Red & Near- IR) read variance depths over vegetation canopies. In the present study, a further index for vegetation identification is proposed. The normalized difference vegetation shortwave index (NDVSI) is defined as the difference between the cubic bands of Near- IR and Shortwave infrared