This study focused on the role and importance of alkaloid compounds in Punica granatum peels which is one of many wide distribution medicinal fruits. Two kinds of pathogenic fungi were isolated from patients in Baghdad to be tested, also a type of extracts was prepared, alkaloids were isolated and partially purified and detected by two ways, a classic depended technique also used for determine these alkaloids, results showed an observed differences among extracts or treatments towards the fungi samples. So this study was one of the scientific applications to find natural alternative compounds that inhibit the growth of several pathogenic organisms that cause dangers and harms for human health.

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

Antibiotic resistance is the major growing threat facing the pharmacological treatment of bacterial infections. Therefore, bioprospecting the medicinal plants could provide potential sources for antimicrobial agents. Mimusops, the biggest and widely distributed plant genus of family Sapotaceae, is used in traditional medicines due to its promising pharmacological activities. This study was conducted to elucidate the antimicrobial effect of three unexplored Mimusops spp. (M. kummel, M. laurifolia and M. zeyheri). Furthermore, the mechanisms underlying such antibacterial activity were studied. The Mimusops leaf extracts revealed significant antibacterial activities against the five tested bacter

This study was done to test the activity of some plant extracts as antioxidant agents. The plants were (Morus rubra, Hibiscus sabdariffa L ., Rhus coriaria L., Anethum graveolens and Petroselinum sativum).
Ethanolic 98% (24 hours/ 25˚c) and distilled water (30 minutes/ 25˚c have been used for extraction.The Total phenols, total flavonoids, total anthocyanin, antioxidant activities were studied.
The extract of Morus rubra was chosen because it has a higher antioxidant activity.
The phenolic extract of Morus rubra was prepare and examined by application it in burger . The antioxidant activity test of Morus rubra was made before and after 3,6 days of cold storage. The sensory evaluation of all treatments were done within 5,1

The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets f

Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol