Evaluation of Intelligent Intrusion Detection Models

This paper discusses an evaluation methodology that can be used to assess the performance of intelligent techniques at detecting, as well as predicting, unauthorised activities in networks. The effectiveness and the performance of any developed intrusion detection model will be determined by means of evaluation and validation. The evaluation and the learning prediction performance for this task will be discussed, together with a description of validation procedures. The performance of developed detection models that incorporate intelligent elements can be evaluated using well known standard methods, such as matrix confusion, ROC curves and Lift charts. In this paper these methods, as well as other useful evaluation approaches, are discussed.Peer reviewe

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets

The density, porosity, breaking force, viscoelastic properties, and the presence or absence of any structural defects or irregularities are important physical-mechanical quality attributes of popular solid dosage forms like tablets. The irregularities associated with these attributes may influence the drug product functionality. Thus, an accurate and efficient characterization of these properties is critical for successful development and manufacturing of a robust tablets. These properties are mainly analyzed and monitored with traditional pharmacopeial and non-pharmacopeial methods. Such methods are associated with several challenges such as lack of spatial resolution, efficiency, or sample-sparing attributes. Recent advances in technology, design, instrumentation, and software have led to the emergence of newer techniques for non-invasive characterization of physical-mechanical properties of tablets. These techniques include near infrared spectroscopy, Raman spectroscopy, X-ray microtomography, nuclear magnetic resonance (NMR) imaging, terahertz pulsed imaging, laser-induced breakdown spectroscopy, and various acoustic- and thermal-based techniques. Such state-of-the-art techniques are currently applied at various stages of development and manufacturing of tablets at industrial scale. Each technique has specific advantages or challenges with respect to operational efficiency and cost, compared to traditional analytical methods. Currently, most of these techniques are used as secondary analytical tools to support the traditional methods in characterizing or monitoring tablet quality attributes. Therefore, further development in the instrumentation and software, and studies on the applications are necessary for their adoption in routine analysis and monitoring of tablet physical-mechanical properties

Rapid design of tool-wear condition monitoring systems for turning processes using novelty detection

Condition monitoring systems of manufacturing processes have been recognised in recent years as one of the key technologies that provide the competitive advantage in many manufacturing environments. It is capable of providing an essential means to reduce cost, increase productivity, improve quality and prevent damage to the machine or workpiece. Turning operations are considered one of the most common manufacturing processes in industry. It is used to manufacture different round objects such as shafts, spindles and pins. Despite recent development and intensive engineering research, the development of tool wear monitoring systems in turning is still ongoing challenge. In this paper, force signals are used for monitoring tool-wear in a feature fusion model. A novel approach for the design of condition monitoring systems for turning operations using novelty detection algorithm is presented. The results found prove that the developed system can be used for rapid design of condition monitoring systems for turning operations to predict tool-wear

An Efficient Approach to EPID Transit Dosimetry

Introduction: In order to maintain uniform standards in the accuracy of fractionated radiation therapy, quantification of the delivered dose per fraction accuracy is required. The pupose of this study was to investigate the feasibility of a transit dosimetry method using the electronic portal imaging device (EPID) for dose delivery error detection and prevention. Methods and Materials: In the proposed method, 2D predicted transit images were generated for comparison with online images acquired during treatment. Predicted transit images were generated by convolving through-air EPID measurements of each field with pixel-specific kernels selected from a library of pre-calculated Monte Carlo pencil kernels of various radiological thicknesses. The kernel used for each pixel was selected based on the calculated radiological thickness of the patient along the line joining the pixel to the virtual source. The accuracy of the technique was evaluated in homogeneous plastic water phantoms, a heterogeneous cylindrical phantom, and an anthropomorphic head phantom. Gamma analysis was used to quantify the accuracy of the technique for the various cases. Results: In the comparison between the measured and predicted images, an average of 99.4% of the points in passed a 3%/ 3 mm gamma for the homogeneous plastic water phantoms. Points for the heterogeneous cylindrical phantom analysis had a 94.6% passing rate. For the anthropomorphic head phantom, an average of 98.3% and 96.6% of points passed the 5%/3mm and 3%/3mm gamma criteria, respectively for all field sizes. Failures occurred typically at points when object thickness was changing rapidly or at boundaries between materials, and at the edges of large fields. Discussion: The results suggested that the proposed transit dosimetry method is a feasible approach to in vivo dose monitoring. The gamma analysis passing rates are within the accuracy needed for transit dosimetry. Future research efforts should include evaluation of the method for more complex treatment techniques and assessment of the sensitivity to changes in EPID or linac hardware, as well as characterization of any dependency the method may have on image ghosting or lag, gantry angle, or long-term stability