Automated Equation Formulation for Causal Loop Diagrams

The annotation of Business Dynamics models with parameters and equations, to simulate the system under study and further evaluate its simulation output, typically involves a lot of manual work. In this paper we present an approach for automated equation formulation of a given Causal Loop Diagram (CLD) and a set of associated time series with the help of neural network evolution (NEvo). NEvo enables the automated retrieval of surrogate equations for each quantity in the given CLD, hence it produces a fully annotated CLD that can be used for later simulations to predict future KPI development. In the end of the paper, we provide a detailed evaluation of NEvo on a business use-case to demonstrate its single step prediction capabilities.

Intelligent DMU creation: Nominal CAD model preparation for automated tolerance allocation

This paper examines the integration of a tolerance design process within the Computer-Aided Design (CAD) environment having identified the potential to create an intelligent Digital Mock-Up [1]. The tolerancing process is complex in nature and as such reliance on Computer-Aided Tolerancing (CAT) software and domain experts can create a disconnect between the design and manufacturing disciplines It is necessary to implement the tolerance design procedure at the earliest opportunity to integrate both disciplines and to reduce workload in tolerance analysis and allocation at critical stages in product development when production is imminent.
The work seeks to develop a methodology that will allow for a preliminary tolerance allocation procedure within CAD. An approach to tolerance allocation based on sensitivity analysis is implemented on a simple assembly to review its contribution to an intelligent DMU. The procedure is developed using Python scripting for CATIA V5, with analysis results aligning with those in literature. A review of its implementation and requirements is presented.

Dynalog: an automated dynamic analysis framework for characterizing android applications

Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

Extending Automated Testing To High-level Software Requirements : A study on the feasibility of automated acceptance-testing

Automated acceptance testing is the testing of software done in higher level to test whether the system abides by the requirements desired by the business clients by the use of piece of script other than the software itself. This project is a study of the feasibility of acceptance tests written in Behavior Driven Development principle. The project includes an implementation part where automated accep- tance testing is written for Touch-point web application developed by Dewire (a software consultant company) for Telia (a telecom company) from the require- ments received from the customer (Telia). The automated acceptance testing is in Cucumber-Selenium framework which enforces Behavior Driven Development principles. The purpose of the implementation is to verify the practicability of this style of acceptance testing. From the completion of implementation, it was concluded that all the requirements from customer in real world can be converted into executable specifications and the process was not at all time-consuming or difficult for a low-experienced programmer like the author itself. The project also includes survey to measure the learnability and understandability of Gherkin- the language that Cucumber understands. The survey consist of some Gherkin exam- ples followed with questions that include making changes to the Gherkin exam- ples. Survey had 3 parts: first being easy, second medium and third most difficult. Survey also had a linear scale from 1 to 5 to rate the difficulty level for each part of the survey. 1 stood for very easy and 5 for very difficult. Time when the partic- ipants began the survey was also taken in order to calculate the total time taken by the participants to learn and answer the questions. Survey was taken by 18 of the employers of Dewire who had primary working role as one of the programmer, tester and project manager. In the result, tester and project manager were grouped as non-programmer. The survey concluded that it is very easy and quick to learn Gherkin. While the participants rated Gherkin as very easy.

Room for Writing: Automated note taking

An introductory exercise to practice when reading papers

Automated Collection of Sign Inventory Information by Integrating Global Positioning System (GPS) with Videologging Data Collection Activities, 1995

Advances in communication, navigation and imaging technologies are expected to fundamentally change methods currently used to collect data. Electronic data interchange strategies will also minimize data handling and automatically update files at the point of capture. This report summarizes the outcome of using a multi-camera platform as a method to collect roadway inventory data. It defines basic system requirements as expressed by users, who applied these techniques and examines how the application of the technology met those needs. A sign inventory case study was used to determine the advantages of creating and maintaining the database and provides the capability to monitor performance criteria for a Safety Management System. The project identified at least 75 percent of the data elements needed for a sign inventory can be gathered by viewing a high resolution image.

Automated generic integration of flight logbook data into aircraft maintenance systems

The automated transfer of flight logbook information from aircrafts into aircraft maintenance systems leads to reduced ground and maintenance time and is thus desirable from an economical point of view. Until recently, flight logbooks have not been managed electronically in aircrafts or at least the data transfer from aircraft to ground maintenance system has been executed manually. Latest aircraft types such as the Airbus A380 or the Boeing 787 do support an electronic logbook and thus make an automated transfer possible. A generic flight logbook transfer system must deal with different data formats on the input side – due to different aircraft makes and models – as well as different, distributed aircraft maintenance systems for different airlines as aircraft operators. This article contributes the concept and top level distributed system architecture of such a generic system for automated flight log data transfer. It has been developed within a joint industry and applied research project. The architecture has already been successfully evaluated in a prototypical implementation.

Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection

Objective: Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. Methods: The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. Results: Post-phenobarbital seizures showed significantly lower amplitude (p < 0.001) and involved fewer EEG channels at the peak of seizure (p < 0.05). No other features or SDA detection rates showed a statistical difference. Conclusion: These findings show that phenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. Significance: The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration.

Automated Discovery of Social Networks in Online Learning Communities

As a way to gain greater insights into the operation of online communities, this dissertation applies automated text mining techniques to text-based communication to identify, describe and evaluate underlying social networks among online community members. The main thrust of the study is to automate the discovery of social ties that form between community members, using only the digital footprints left behind in their online forum postings. Currently, one of the most common but time consuming methods for discovering social ties between people is to ask questions about their perceived social ties. However, such a survey is difficult to collect due to the high investment in time associated with data collection and the sensitive nature of the types of questions that may be asked. To overcome these limitations, the dissertation presents a new, content-based method for automated discovery of social networks from threaded discussions, referred to as ‘name network’. As a case study, the proposed automated method is evaluated in the context of online learning communities. The results suggest that the proposed ‘name network’ method for collecting social network data is a viable alternative to costly and time-consuming collection of users’ data using surveys. The study also demonstrates how social networks produced by the ‘name network’ method can be used to study online classes and to look for evidence of collaborative learning in online learning communities. For example, educators can use name networks as a real time diagnostic tool to identify students who might need additional help or students who may provide such help to others. Future research will evaluate the usefulness of the ‘name network’ method in other types of online communities.

The role of automated sorting in the recovery of aluminium alloys waste

Selected papers from the 3rd Edition of the International Conference on Wastes: Solutions, Treatments and Opportunities

'Cooperative Automated worm Response and Detection ImmuNe ALgorithm (CARDINAL) inspired by T-cell Immunity and Tolerance'

The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three central T-cell processes, namely T-cell maturation, differentiation and proliferation, naturally map into this domain and further illustrate how such an algorithm fits into a complete immune inspired computer security system and framework.

Automated Software Debugging Using Hybrid Static/Dynamic Analysis

With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.

Microstructure and tensile properties of carbon-epoxy laminates produced by automated fibre placement: Influence of a caul plate on the effects of gap and overlap embedded defects

Automated fibre placement (AFP) enables the trajectory of unidirectional composite tape to be optimized, but laying down complex shapes with this technology can result in the introduction of defects. The aim of this experimental study is to investigate the influence of gaps and overlaps on the microstructure and tensile properties of carbon-epoxy laminates. First, a comparison between a hand-layup and AFP layup, draped and cured under the same conditions, shows equivalent microstructures and tensile properties. This provides the reference values for the study. Then, gap and overlap embedded defects (more or less severe) are introduced during manufacturing, on two cross-ply layups [(0°/(90°)5/0°] and [(90°/0°)2/90°]. Autoclave cure without a caul plate results in local thickness variation and microstructural changes which depend on the defect type. This has a strong influence on mechanical performance. Use of a caul plate avoids these variations and in this case embedded defects hardly affect tensile properties.