The results shows existence of metals such as copper, iron, Cadmium, lead and zinc in most of examined samples , the highest concentration are up to (2.26, 40.82, 282.5, 31.02, 19.26, 4.34) Part per million) ppm) in pasta hot (Zer brand), Indomie with chicken, granule (Zer brand), brand (Zer brand), and rice (mahmood brand) respectively, with presence nickel in spaghetti( Zer brand), granule, Zer brand with concentration reached to 4.34 ppm and 1.06 ppm respectively.
The results of cereals group and its products show that two kinds of fungi, Aspergillus spp. and Penicillin spp. were found in rice (Mahmood brand) with numbers got to 1.5×103 Colony Forming Unit/ gram (c.f.u./g),while Bacillus cereus and Staphylococcus aureus were isola

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

BACKGROUND: CRC is one of the most common cancers in the world. K-ras is proto-oncogene with GTPase activity that is lost when the gene is mutated. Analysis of K-ras mutational status is very important for CRC treatment, being the most important predictors of resistance to targeted therapy. OBJECTIVE: This study aims to determine the frequency and spectrum of K-ras mutation among Iraqi patients with sporadic CRC. PATIENTS, MATERIALS AND METHODS: This study enrolled 35 cases with sporadic CRC; their clinicopathological parameters were analyzed. The FFPE blocks were used for DNA extraction; PCR amplification of K-ras gene and hybridization of allele-specific oligoprobes were performed. The assay covers 29 mutations in the K-ras gene (codons 1

Many studies have been published to address the growing issues in wireless communication systems. Space-Time Block Coding (STBC) is an effective and practical MIMO-OFDM application that can address such issues. It is a powerful tool for increasing wireless performance by coding data symbols and transmitting diversity using several antennas. The most significant challenge is to recover the transmitted signal through a time-varying multipath fading channel and obtain a precise channel estimation to recover the transmitted information symbols. This work considers different pilot patterns for channel estimation and equalization in MIMO-OFDM systems. The pilot patterns fall under two general types: comb and block types, with

Global Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufacturers, were fi

Global Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufactur

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre