Problem-based learning as an effective tool for teaching computer network design

This paper addresses the challenge of developing techniques for the effective teaching of computer network design. It reports on the experience of using the technique of problem-based learning as a key pedagogical method for teaching practical network design within the context of a Master's program module in data telecommunications and networks at the University of Salford, Salford, Greater Manchester, U.K. A two-threaded approach was adopted that comprised a problem-based learning thread and a conventional lecture thread. The problem-based learning thread within the module comprised sessions designed to place the students in the position of network design consultants who are introduced to scenarios that have a high degree of realism in which a client has specific business requirements that can be met through the adoption of a network solution. In this way, the problem-based learning thread allows the students to develop their design skills, while the lecture thread uses traditional teaching methods to allow students to develop their understanding of key network components and architectures. A formal evaluation of this approach has been carried out and demonstrated a very effective and realistic learning experience for the students. Therefore, the authors propose that problem-based learning is an ideal pedagogical tool for the teaching of computer network design

Pulsatile spiral blood flow through arterial stenosis

Pulsatile spiral blood flow in a modelled three-dimensional arterial stenosis, with a 75% cross-sectional area reduction, is investigated by using numerical fluid dynamics. Two-equation k-ω model is used for the simulation of the transitional flow with Reynolds numbers 500 and 1000. It is found that the spiral component increases the static pressure in the vessel during the deceleration phase of the flow pulse. In addition, the spiral component reduces the turbulence intensity and wall shear stress found in the post-stenosis region of the vessel in the early stages of the flow pulse. Hence, the findings agree with the results of Stonebridge et al. (2004). In addition, the results of the effects of a spiral component on time-varying flow are presented and discussed along with the relevant pathological issues

Active router approach to defeating denial-of-service attacks in networks

Denial-of-service attacks represent a major threat to modern organisations who are increasingly dependent on the integrity of their computer networks. A new approach to combating such threats introduces active routers into the network architecture. These active routers offer the combined benefits of intrusion detection, firewall functionality and data encryption and work collaboratively to provide a distributed defence mechanism. The paper provides a detailed description of the design and operation of the algorithms used by the active routers and demonstrates how this approach is able to defeat a SYN and SMURF attack. Other approaches to network design, such as the introduction of a firewall and intrusion detection systems, can be used to protect networks, however, weaknesses remain. It is proposed that the adoption of an active router approach to protecting networks overcomes many of these weaknesses and therefore offers enhanced protection

Ensuring the Full Freedom of Religion on Public Lands: Devils Tower and the Protection of Indian Sacred Sites

Federal land management agencies historically have disregarded American Indian cries for protection of sacred sites on public lands, and the federal judiciary consistently has supported such action according to a formalistic interpretation of the Religion Clauses of the First Amendment. This Note takes issue with the pattern of religious oppression in the context of public land management by positing a more inclusive, “full,” conception of religious freedom under the First Amendment. This Note then analyzes the recent controversy at Devils Tower National Monument as an important opportunity to break the trend and embrace Indian religious freedoms around sacred sites on public lands

Effect of In ovo Injection of Probiotic, Prebiotic, and Synbiotic on Growth Performance and Gut Health Parameters of Broiler Chicken.

M.S. Thesis. University of Hawaiʻi at Mānoa 2018

Review of either, Orpheus by Dan Disney

Review of either, Orpheus by Dan Disne

Explorative Analysis and Data Mining in Big Neural Data

Most motor actions are carried out by many neurons acting together in different areas of the brain. Recently, techniques have been developed and increasingly used that allow simultaneous recordings of the activity from a large number of neurons over time ranges as long as several weeks. At Neuronano Research Center (NRC) at Lund University, neural activity in rodents has been recorded using chronically implanted 128-channel electrodes. The targets are within areas that play a prominent role in the planning, monitoring and execution of movements and, consequently, are strongly affected by motor diseases such as Parkinson’s disease. The experiments conducted at NRC naturally produces a large amount of neural data. This master thesis work aims to perform feature extraction from that data, i.e., find a way to mathematically describe the disease states of the rodents without a priori knowledge of the states. This is done by extracting features from the recordings, whose values later are used to analyse and cluster the data. The results show that a clear majority of the neurons exhibit a significant difference in feature values between the disease states. This means that it is possible to mathematically describe the different disease states. Moreover, the results show that different neurons behave differently: Some, e.g., exhibit increased activity going from one state to another, while others exhibit decreased activity. Adding to this, some does not exhibit any change while others exhibit a significant change. That it is possible to mathematically describe the different disease states, with a timescale of hours, indicate that the same may be possible for states with smaller timescales. These states, with a smaller timescale, do not have to be connected to Parkinson’s disease but could rather be normal, healthy states such as locomotion or reaching.Parkinson’s – a mathematical description In search for answers to how the brains of Parkinson patients function there are not many tools available. One of them proves to be mathematics. Another is rodent experiments, which play an important and necessary role in the process of finding new treatments for the disease. Research indicate that, in rodents, it is possible to distinguish between different states of health and disease by using mathematical analysis. This can be done by analysing the brain signals of the animal, and this without knowing what state the animal is in at that time. It seems possible to use mathematics to describe different states of health and disease, opening up new possibilities on the road to finding new treatments. But, how does this actually work? Parkinson’s disease is the second most common degenerative disease. It damages the brain with consequences such as impaired movements, tremors at rest, dementia and, finally, 10 to 20 years later, death. The knowledge of exactly how the area of the brain affected by Parkinson’s works is unfortunately still limited. Better knowledge could lead to the development of new treatments, hopefully with less side effects than those currently used. The brain is the part of our body that controls our thoughts, feelings and actions. It interprets, helping us to make sense of the world, and controls actions such as breathing, talking and moving (to mention very few). Our actions, including movements, are controlled by the use of nerve cells, called neurons, connected to each other in a complicated network. The neurons use this network to communicate with each other by sending and receiving electrical signals: action potentials. At Neuronano Research Center (NRC), Lund University, a group of scientists has found a way to perform the very challenging task of recording the signals from a lot of these tiny neurons. The brain signals recorded are from rats and, specifically, from neurons in an area of their brain that controls movements. The reason that this area has been chosen is that it is strongly affected by diseases that impair our movements, such as Parkinson’s disease. The rats used in the experiments at NRC have received drug injections infecting half of their brains with Parkinson’s disease. In this way, the healthy half of the brain can be used as a reference when analysing what happens in the other, diseased half. During the experiments, action potentials from neurons in both the healthy and diseased part of the brain are recorded and saved, resulting in a very large dataset. The amount of action potentials, as well as the pattern that they are fired in affects the message being sent. Let us look at a simple example: A sequence of action potentials, sent from a neuron, can be represented by ones and zeros. A one is an action potential and a zero means that nothing happened at that time: 1 1 0 1 1 0 1 1 0 1 1 0 0 1 1 0 0 0 1 0 1 0 0 1 The first sequence consists of two ones followed by a zero whereas the second does not follow any obvious pattern. Also, the first one has more action potentials (eight) than the other has (five). These properties, among many others, can easily be expressed mathematically. It has been found that the sequences of action potentials change when the behaviour changes: The meaning of a certain sequence from a certain neuron is not yet known, but maybe it will be in the future! But, the fact that sequences change when the behaviour of the animal changes is a strong motivation to continue the search: Answers to how our brains function and new treatments for diseases can be uncovered by means of mathematics