Triticale is a hybrid of wheat and rye grown for use as animal feed. In Florida, due to its soft coat, triticale is highly vulnerable to Sitophilus oryzae L. (rice weevil) and there is interest in development of methods to detect early-instar larvae so that infestations can be targeted before they become economically damaging. The objective of this study was to develop prediction models of the infestation degree for triticale seed infested with rice weevils of different growth stages. Spectral signatures were tested as a method to detect rice weevils in triticale seed. Groups of seeds at 11 different levels (degrees) of infestation, 0–62%, were obtained by combining different ratios of infested and uninfested seeds. A spectrophotometer wa

The present study was performed to evaluate the level of some risk factors (biochemical and immunological) in hypothyroid Iraqi patients considering the different thyroid functional states (hypothyroidism and subclinical hypothyroidism).The study includes 82 patients clinically diagnosed with hypothyroidism. Three study groups have been investigated: (47 clinical hypothyroid patients, 12 subclinical hypothyroid patients 23 healthy individuals) of different ages. This study, show that the proportion of females (83.3 %), (87.2%) in subclinical and clinical hypothyroidisim respectively higher than the proportion of males (16.7%),(12.8%) in subclinical and clinical hypothyrodism respectively of the total patients.The majority of subclinical hyp

The target of this study was to study the natural phytochemical components of the head (capsule) of Cynara scolymus cultivated in Iraq. The head (capsule) of plant was extracted by maceration in70% ethanol for 72 hours, and fractioned by hexane, chloroform and ethyl acetate. Preliminary qualitative phytochemical screening was performed on the ethyl acetate fraction for capsule was revealed the presence of flavonoid and aromatic acids. These were examined by (high -performance liquid chromatography) (HPLC diodarray), (high- performance thin-layer chromatography)(HPTLC).

Flavonoids were isolated by preparative layer chromatography and aromatic acid was isolated by preparative high-

The telecommunications industry has gone through series of development efforts to provide quality services to their consumers. Generally, telecommunication industry provides two main services such as telephony and internet which involved customer registration, billing and payment. However, the challenge confronting telecommunications industry is to meet the customer satisfaction in the billing system such as accuracy, easy to understand and unambiguous billing issue. In order to develop Customer Billing Telephony System,a user experience study is conducted to gather the user requirements. Hence, the CBTS was developed that takes into consideration user’s value experience that provides a support for managing and monitoring billing proce

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob