The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.
In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.
Urinary tract infections (UTI) are some of the most common infections experienced by humans, exceeded in frequency among ambulatory patient only by respiratory and gastrointestinal infections. It is also the most common cause of nosocomial infection in adults. A total of three hundred urine sample were collected in age (1-69 years old) in both gender, with (UTI) symptoms referred to AL-Yarmok Teaching Hospital at Baghdad city during the period from January 2010 till August 2010. The commonest isolates were Escherichia coli (E.Coli), Proteus mirabilis and Klebsiella pneumoniae (These represented 49.2%, 22 %, and16 % of isolates respectively). The percentage of bacteria incidence in females
... Show MoreThere is not enough studies about bacterial contamination of air condition system in the cars and houses, bacterial detection of such surrounding is necessary for the human environment.
The object of recent study was to evaluate the level of bacterial contamination in air conditioner in cars and houses in Baghdad city, Iraq.
Air samples were taken indoor from cars and house air conditioner in the Baghdad city. The result indicated that gram positive bacteria more than gram negative bacteria in air conditioner. Air condition of cars (20-500 CFU) was more contaminated than of houses (10-100 CFU).
Bacillus was the most frequently bacterial isolates genus with recovery rate B
... Show MoreBackground: Candida tropicalis is one of the most causes of vulvovaginal candidiasis (VVC) in women. Systemic candidiasis and candidemia may also occur in pregnancies. Objective: This study was carried out to detect and isolate of this yeast from aborted placenta, which may cause severe complications such as spontaneous abortion. Materials and methods: Fresh aborted placenta were collected and washed by normal saline to remove the blood. Then, cut it into portions and place it in test tube containing 5 ml of normal saline. Finally, shake for 10 minutes, after that, cultured for microbial isolation. Isolation and detection were done by some conventional methods with Api candida and CHROMagar. Results: The results showed that four iso
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Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The res
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The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.
This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviatin
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Karbala province was one of the most important areas in Iraq and considered an
economic resource of vegetation such as trees of fruits, sieve and other vegetation.
This research aimed to utilize change detection for investigating the current
vegetation cover at last three decay. The main objectives of this research are collect
a group of studied area (Karbala province) satellite images in sequence time for
the same area, these image captured by Landsat (TM 1995, ETM+ 2005 and
Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such as atmosphere
correction and rectification has been done. Mosaic model between the parts of
studied area was performing. Gap filling consider being very important step has
be
This study was conducted to evaluate the prevalence rate of
toxoplasmosis among 294 rheumatoid arthritis (RA) patients treated with
methotrexate (MTX), 50 RA patients without treatment and 50 samples as
healthy control. Blood samples were collected and the presence of T.gondii
IgG and IgM antibodies was determined by using Enzyme linked
immunosorbent assay (ELISA). Tumor necrosis factor alpha (TNF-α) was
also estimated in serum of all subjects by using ELISA method too. The
seroprevalence of toxoplasmosis IgM and IgG in RA+MTX was
60(20.408%), and 98(33.33%), in RA patients 4(8%), and 18(36%) while,
it was 2(24%), 6(12%) in healthy group. Tumor necrosis factor alpha
(TNF-α) was also estimated in serum of a
A total of 90 stool sample was collected from patients with gastroenteritis to
detect adenovirus antigen among diarrhea cases. They were tested by general stool
examination (GSE), rapid immunochromatographic test and Enzyme Linked
Immunosorbent Assay (ELISA). GSE showed that adenovirus gastroenteritis
infection resulted in non-bloody diarrhea, the existence of RBCs in 7% and Pus in
37% of the samples, Entamoeba histolytica trophozoite and cyst were seen in 3%
and 2% of the samples respectively. The rapid test showed that 21% of samples
were positive for rotavirus, 8% for adenovirus and 3% for astrovirus. Meanwhile,
the ELISA test showed that adenovirus was positive in 9% of the samples. These
findings establish