Multimedia applications impose different QoS requirements (e.g., bounded end-to-end delay and jitter) and need an enhanced transport layer protocol that should handle packet loss, minimize errors, manage network congestion, and transmit efficiently. Across an IP network, the transport layer protocol provides data transmission and affects the QoS provided to the application on hand. The most common transport layer protocols used by Internet applications are TCP and UDP. There are also advanced transport layer protocols such as DCCP and TFRC. The authors evaluated the performance of UDP, DCCP, SCTP, and TFRC over wired networks for three traffic flows: data transmission, video streaming, and voice over IP. The evaluation criteria were throughput, end-to-end delay, and packet loss ratio. They compared their performance to learn in which traffic flow/service each of these protocols functions better than the others. The throughput of SCTP and TFRC is better than UDP. DCCP is superior to SCTP and TFRC in terms of end-to-end delay. SCTP is suitable for Internet applications that require high bandwidth.
The aim of the present study is to highlight the role of total cholesterol (TC), triacylglycerol (TG), Glycated hemoglobin A1c and iron in Iraqi women with multiple sclerosis and also to examine the biochemical action of copaxone (which is the most widely used in the 21st century to treat multiple sclerosis) on these biochemical parameters. This is the first study in Iraq which deals copaxone action on TC , TG , HbA1c and iron. Ninety women in their fourth decade suffering from multiple sclerosis were enrolled in this study. They were divided into: the first (group B) composed of (30) women without any treatment related to multiple sclerosis or any treatment linked with chronic or inflammatory diseases. The second (group A1) included (30)
... Show MoreThe present work aimed to study the effect of Grave's disease on the different tissues and organs of the body by using Wayne Thyrotoxicosis Diagnostic Index (WTDI) and Basel Metabolic Index (BMI). To reach such aim, (35) patients were involved (25 females and 10 males). A control group of (15) healthy individuals (10 females and 5 males) was selected for comparison , as well as , the following: 1- Wayne Thyrotoxicosis Diagnostic Index (WTDI) applied on patient group and control group under the supervision of specialist medical team , this index include (19) sign and symptom , the appearance of one of them may be lead to the others. The sings and symptoms of the index appear only on the patients. There is no Significant di
... Show MoreDAIRMD Professor Hayder R. Al-Hamamy, **Professor Adil A. Noaimi, **Dr. Ihsan A. Al-Turfy, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015
HR Al-Hamamy, AA Noaimi, IA Al-Turfy, AI Rajab, Journal of Cosmetics, Dermatological Sciences and Applications, 2015
The research aimed mainly to discover the effectiveness of the (PEOE) model in teaching science to develop the skills of generating and evaluating information and the emotional side of the scientific sense of the intermediate first grade students. An experimental approach with a quasi-experimental design called pre-test and post-test control design was used. The research sample consisted of (60) students, who were selected in a random cluster method, (30) students in the experimental group studied the unit "The Nature of Material" using the (PEOE) model, and (30) students in the control group studied according to the prevailing method of teaching. The research materials and tools were represented in: a teacher's guide for teaching the un
... Show MoreTwelve N-(6-sustirured benzothanol-2-y1) succinamic acids and 3-(6-substitted benzonathol-2-y1)-carbamoyl propionyl chloride were synthesized in good yields from reaction of benzonathol2-yl)
Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
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