Computing with CodeRunner at Coventry University:Automated summative assessment of Python and C++ code.

CodeRunner is a free open-source Moodle plugin for automatically marking student code. We describe our experience using CodeRunner for summative assessment in our first year undergraduate programming curriculum at Coventry University. We use it to assess both Python3 and C++14 code (CodeRunner supports other languages also). We give examples of our questions and report on how key metrics have changed following its use at Coventry.Comment: 4 pages. Accepted for presentation at CEP2

Local Cooperatives' Role in the Identity-Preserved Grain Industry

This study examines how locally owned cooperatives have responded to the transition from commodity to identity-preserved grain marketing. Survey results showed locals’ overall commitment to identity-preserved grains was determined more by a cultural receptivity to innovation than by differences in priorities among grain, feed, and general managers.cooperatives, grain, identity-preserved grain, specialty grain, innovation, Crop Production/Industries,

Looking Ahead: Workforce Supply/Demand Analysis for New Jersey's Pharmaceutical and Medical Technology Industries

This analysis presents the results of a workforce supply and demand analysis of the pharmaceutical and medical technology industries in New Jersey

The Separation of Facts and Values

Dr. Kantrowitz maintains that much modern pessimism derives from failure to separate what is from what ought to be and urges that scientific conflicts be resolved as value neutrally as possible

The Political Economy of Industrial Policy in China: The Case of Aircraft Manufacturing

Since 1960, only one new country, Brazil, has succeeded in delivering more than one civil jet per month. Otherwise, all the countries now offering world-class planes were established in aviation by the end of World War I. This being said, low-cost producers within several of the newly emerging markets have already acquired front-end manufacturing expertise as a direct result of industrial offset contracts and/or other forms of technology transfer. In all such cases, government intervention, notably through state ownership, has been predominant, but failures have been numerous in view of the difficulty of aligning ownership structure to financial, managerial, and technological requirements and of garnering the support of domestic interest groups. In this paper the focus is China’s efforts to build a world-class aircraft manufacturing industry. In the first half of the 1990s the potential of the Chinese industry to mount a competitive challenge to Western aircraft builders was largely discounted. Nowadays, as China strives to bear the ARJ-21 project to execution and even considers entering the market for wide-bodies, the threat is taken more seriously. The growth in the Chinese air transport market has reinforced the bargaining power of national aircraft producers and authorities are giving priority to building science and technology capacity in this area. Progress in creating military/civilian synergies has proven much more modest – especially when compared to the shipbuilding industry – and better coordination in the overall industry comes a distant fourth in the explanations’ peaking order.http://deepblue.lib.umich.edu/bitstream/2027.42/40165/3/wp779.pd

Intrusion Detection System using Bayesian Network Modeling

Computer Network Security has become a critical and important issue due to ever increasing cyber-crimes. Cybercrimes are spanning from simple piracy crimes to information theft in international terrorism. Defence security agencies and other militarily related organizations are highly concerned about the confidentiality and access control of the stored data. Therefore, it is really important to investigate on Intrusion Detection System (IDS) to detect and prevent cybercrimes to protect these systems. This research proposes a novel distributed IDS to detect and prevent attacks such as denial service, probes, user to root and remote to user attacks. In this work, we propose an IDS based on Bayesian network classification modelling technique. Bayesian networks are popular for adaptive learning, modelling diversity network traffic data for meaningful classification details. The proposed model has an anomaly based IDS with an adaptive learning process. Therefore, Bayesian networks have been applied to build a robust and accurate IDS. The proposed IDS has been evaluated against the KDD DAPRA dataset which was designed for network IDS evaluation. The research methodology consists of four different Bayesian networks as classification models, where each of these classifier models are interconnected and communicated to predict on incoming network traffic data. Each designed Bayesian network model is capable of detecting a major category of attack such as denial of service (DoS). However, all four Bayesian networks work together to pass the information of the classification model to calibrate the IDS system. The proposed IDS shows the ability of detecting novel attacks by continuing learning with different datasets. The testing dataset constructed by sampling the original KDD dataset to contain balance number of attacks and normal connections. The experiments show that the proposed system is effective in detecting attacks in the test dataset and is highly accurate in detecting all major attacks recorded in DARPA dataset. The proposed IDS consists with a promising approach for anomaly based intrusion detection in distributed systems. Furthermore, the practical implementation of the proposed IDS system can be utilized to train and detect attacks in live network traffi

How to entrain your evil demon

The notion that the brain is a prediction error minimizer entails, via the notion of Markov blankets and self-evidencing, a form of global scepticism — an inability to rule out evil demon scenarios. This type of scepticism is viewed by some as a sign of a fatally flawed conception of mind and cognition. Here I discuss whether this scepticism is ameliorated by acknowledging the role of action in the most ambitious approach to prediction error minimization, namely under the free energy principle. I argue that the scepticism remains but that the role of action in the free energy principle constrains the demon’s work. This yields new insights about the free energy principle, epistemology, and the place of mind in nature