SMA -- The Smyle Modeling Approach

This paper introduces the model-based software development lifecycle model SMA -- the Smyle Modeling Approach -- which is centered around Smyle. Smyle is a dedicated learning procedure to support engineers to interactively obtain design models from requirements, characterized as either being desired (positive) or unwanted (negative) system behavior. Within SMA, the learning approach is complemented by so-called scenario patterns where the engineer can specify clearly desired or unwanted behavior. This way, user interaction is reduced to the interesting scenarios limiting the design effort considerably. In SMA, the learning phase is further complemented by an effective analysis phase that allows for detecting design flaws at an early design stage. Using learning techniques allows us to gradually develop and refine requirements, naturally supporting evolving requirements, and allows for a rather inexpensive redesign in case anomalous system behavior is detected during analysis, testing, or maintenance. This paper describes the approach and reports on first practical experiences

Performance Metrics for Network Intrusion Systems

Intrusion systems have been the subject of considerable research during the past 33 years, since the original work of Anderson. Much has been published attempting to improve their performance using advanced data processing techniques including neural nets, statistical pattern recognition and genetic algorithms. Whilst some significant improvements have been achieved they are often the result of assumptions that are difficult to justify and comparing performance between different research groups is difficult. The thesis develops a new approach to defining performance focussed on comparing intrusion systems and technologies. A new taxonomy is proposed in which the type of output and the data scale over which an intrusion system operates is used for classification. The inconsistencies and inadequacies of existing definitions of detection are examined and five new intrusion levels are proposed from analogy with other detection-based technologies. These levels are known as detection, recognition, identification, confirmation and prosecution, each representing an increase in the information output from, and functionality of, the intrusion system. These levels are contrasted over four physical data scales, from application/host through to enterprise networks, introducing and developing the concept of a footprint as a pictorial representation of the scope of an intrusion system. An intrusion is now defined as “an activity that leads to the violation of the security policy of a computer system”. Five different intrusion technologies are illustrated using the footprint with current challenges also shown to stimulate further research. Integrity in the presence of mixed trust data streams at the highest intrusion level is identified as particularly challenging. Two metrics new to intrusion systems are defined to quantify performance and further aid comparison. Sensitivity is introduced to define basic detectability of an attack in terms of a single parameter, rather than the usual four currently in use. Selectivity is used to describe the ability of an intrusion system to discriminate between attack types. These metrics are quantified experimentally for network intrusion using the DARPA 1999 dataset and SNORT. Only nine of the 58 attack types present were detected with sensitivities in excess of 12dB indicating that detection performance of the attack types present in this dataset remains a challenge. The measured selectivity was also poor indicting that only three of the attack types could be confidently distinguished. The highest value of selectivity was 3.52, significantly lower than the theoretical limit of 5.83 for the evaluated system. Options for improving selectivity and sensitivity through additional measurements are examined.Stochastic Systems Lt

Digitized and computerized recordkeeping in dentistry (Orthodontics) : A Technologically Advanced Alternative to the Analysis and Storage of Study Models

Magister Scientiae Dentium - MSc(Dent)The research is aimed at investigating and finding alternatives to the physical necessity of producing and storing plaster casts or stone models of the tissues of the mouth. The quest for time and space is universal and the successful management of both results in stress free, financially stable and uncluttered work circumstances. Study models do playa very important role in diagnostics and treatment planning as well as communicating final results in Dentistry, especially in Orthodontic practice. Conventional study models are bulky, fragile, and expensive diagnostic tools produced from impressions taken of the patient's mouth and cast in plaster or stone. The storage of these records creates major space problems, and recalling or retrieving models at some later stage also causes logistical problems. Ideally, the tissues of the mouth could be scanned and from this a 3-D image produced on screen, which could later be milled (machining process of reproducing, explained in Appendix B) if necessary. Three dimensionally accurate, visually pleasing, reproducible, measurable and retrievable records, would be the solution. Computerizing dental records has already revolutionized the industry in the fields of Radiology and written patient data. This information is available at the click of a mouse, and integrated diagnostic tools can be displayed on screen. A thorough investigation of all methods of capturing dental data and 3D images from previously researched and publicized studies was conducted before attempting the latest technology. The final project involved: 1. requesting an introductory and explanatory demonstration on the scanning possibilities in South Africa 2. organizing and attending a demonstration of the laser and contact scanner on study models and impressions. 3. undergoing training in the use of a contact scanner. Computerizing of these results and comparing data derived from analyzing both study models and impressions, manually and digitally. 4. researching and collecting of data with engineering professionals, to establish the validity and viability of this method ( aiming to use uncomplicated, widely accepted and thoroughly applicable basic criteria in all experiments.) 5. evaluation of data statistically by a statistician. Discussion: Digitizing and computerizing of images derived from scanning the models or impressions offers the most attractive alternative for record keeping. Laser scanning disappointed in general due to the relative unavailability in South Africa, the expensive nature of the service elsewhere and limiting factors due to the sensitivity of the laser beam. It is the most promising alternative in future research, because of improved accuracy, higher speed of scanning, uniformity and reproducibility. Contact scanning proved to be available, reliable and adjustable. In most applications, the best results in terms of accuracy and quality of surface finish are obtained using contact scanning. The disadvantage of this method is the time factor and therefore it becomes expensive and economically not viable. The direct scanning of impressions, albeit with laser or contact scanning, remains a scientific and clinical viable option. Conclusion: Digital imaging is still a young technology and many aspects are not yet completely explored. It is a promising technology and its significance is increasing because it opens the door to diagnostic information. Another important development is that the software for digital imaging will become more integrated with other computerized dental applications in the dental office, enabling patient data between different and remote practices to be exchanged more easily. Further progress is not limited by a lack of available image processing tools but rather by our restricted understanding of the various components of diagnostic imaging in dentistry. A Bioengineering exhibition mounted by the University of Munich during a December 2000 conference, displayed a specially adapted CT Scanner that could scan information directly from the mouth. This leads to more possibilities of deriving images without impressions or study casts

MSCan: A tool for analyzing MSC specifications

Abstract. We present the tool MSCan, which supports MSC-based system development. In particular, it automatically checks high-level MSC specifications for implementability.

Advanced Energy Harvesting Technologies

Energy harvesting is the conversion of unused or wasted energy in the ambient environment into useful electrical energy. It can be used to power small electronic systems such as wireless sensors and is beginning to enable the widespread and maintenance-free deployment of Internet of Things (IoT) technology. This Special Issue is a collection of the latest developments in both fundamental research and system-level integration. This Special Issue features two review papers, covering two of the hottest research topics in the area of energy harvesting: 3D-printed energy harvesting and triboelectric nanogenerators (TENGs). These papers provide a comprehensive survey of their respective research area, highlight the advantages of the technologies and point out challenges in future development. They are must-read papers for those who are active in these areas. This Special Issue also includes ten research papers covering a wide range of energy-harvesting techniques, including electromagnetic and piezoelectric wideband vibration, wind, current-carrying conductors, thermoelectric and solar energy harvesting, etc. Not only are the foundations of these novel energy-harvesting techniques investigated, but the numerical models, power-conditioning circuitry and real-world applications of these novel energy harvesting techniques are also presented

Diagnostics in Plant Breeding

“Diagnostics in Plant Breeding” is systematically organizing cutting-edge research reviews on the development and application of molecular tools for the prediction of plant performance. Given its significance for mankind and the available research resources, medical sciences are leading the area of molecular diagnostics, where DNA-based risk assessments for various diseases and biomarkers to determine their onset become increasingly available. So far, most research in plant genomics has been directed towards understanding the molecular basis of biological processes or phenotypic traits. From a plant breeding perspective, however, the main interest is in predicting optimal genotypes based on molecular information for more time- and cost-efficient breeding schemes. It is anticipated that progress in plant genomics and in particular sequence technology made recently will shift the focus from “explanatory” to “predictive” in crop science. This book assembles chapters on all areas relevant to development and application of predictive molecular tools in plant breeding by leading authorties in the respective areas