To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

The syntheses, characterization and experimental solid state X-ray structures of five low-spin paramagnetic 2-pyridyl-(1,2,3)-triazole-copper compounds, [Cu(Ln)2Cl2], are presented in this study, for the following five Ln ligands: L1 = 2-(1-(p-tolyl)-1H-(1,2,3-triazol-4-yl)pyridine), L2 = 2-(1-(4- chlorophenyl)-1H-(1,2,3-triazol-4-yl)pyridine), L3 = 4-(4-(pyridin-2-yl)-1H-(1,2,3-triazol-4-yl)benzonitril), L4 = 2-(1-phenyl-1H-(1,2,3-triazol-4-yl)pyridine) and L5 = 2-(1-(4-(trifluoromethyl)phenyl)-1H-(1,2,3- triazol-4-yl)pyridine). These five [Cu(Ln)2Cl2] complexes each contain two bidentate 2-pyridyl-(1,2,3)- triazole (Ln) and two chloride ions as ligands, with the Cu–N(pyridine) bonds, Cu–N(triazole) and Cu–Cl bonds trans to each othe

NA Nasir, SHM Ali, HQMA AL-Ess, WA Hussein, MKW Al-Janabi, KIA Mohammed, JM Mosa, Euromediterranean Biomedical Journal, 2020

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq