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This thesis emphasizes problems that reports generated by vulnerability scanners impose on the process of vulnerability management, which are a. an overwhelming amount of data and b. an insufficient prioritization of the scan results.
To assist the process of developing means to counteract those problems and to allow for quantitative evaluation of their solutions, two metrics are proposed for their effectiveness and efficiency. These metrics imply a focus on higher severity vulnerabilities and can be applied to any simplification process of vulnerability scan results, given it relies on a severity score and time of remediation estimation for each vulnerability.
A priority score is introduced which aims to improve the widely used Common Vulnerability Scoring System (CVSS) base score of each vulnerability dependent on a vulnerability’s ease of exploit, estimated probability of exploitation and probability of its existence.
Patterns within the reports generated by the Open Vulnerability Assessment System (OpenVAS) vulnerability scanner between vulnerabilities are discovered which identify criteria by which they can be categorized from a remediation actor standpoint. These categories lay the groundwork of a final simplified report and consist of updates that need to be installed on a host, severe vulnerabilities, vulnerabilities that occur on multiple hosts and vulnerabilities that will take a lot of time for remediation. The highest potential time savings are found to exist within frequently occurring vulnerabilities, minor- and major suggested updates.
Processing of the results provided by the vulnerability scanner and creation of the report is realized in the form of a python script. The resulting reports are short, straight to the point and provide a top down remediation process which should theoretically allow to minimize the institutions attack surface as fast as possible. Evaluation of the practicality must follow as the reports are yet to be introduced into the Information Security Management Lifecycle.
The influence of sleep on human life, including physiological, psychological, and mental aspects, is remarkable. Therefore, it is essential to apply appropriate therapy in the case of sleep disorders. For this, however, the irregularities must first be recognised, preferably conveniently for the person concerned. This dissertation, structured as a composition of research articles, presents the development of mathematically based algorithmic principles for a sleep analysis system. The particular focus is on the classification of sleep stages with a minimal set of physiological parameters. In addition, the aspects of using the sleep analysis system as part of the more complex healthcare systems are explored. Design of hardware for non-obtrusive measurement of relevant physiological parameters and the use of such systems to detect other sleep disorders, such as sleep apnoea, are also referred to. Multinomial logistic regression was selected as the basis for development resulting from the investigations carried out. By following a methodical procedure, the number of physiological parameters necessary for the classification of sleep stages was successively reduced to two: Respiratory and Movement signals. These signals might be measured in a contactless way. A prototype implementation of the developed algorithms was performed to validate the proposed method, and the evaluation of 19324 sleep epochs was carried out. The results, with the achieved accuracy of 73% in the classification of Wake/NREM/REM stages and Cohen's kappa of 0.44, outperform the state of the art and demonstrate the appropriateness of the selected approach. In the future, this method could enable convenient, cost-effective, and accurate sleep analysis, leading to the detection of sleep disorders at an early stage so that therapy can be initiated as soon as possible, thus improving the general population's health status and quality of life.
Die digitale Transformation von Geschäftsprozessen und die stärkere Einbindung von IT-Systemen erzeugen bei kleinen und mittelständischen Unternehmen (KMU) Chancen und Risiken zugleich. Risiken, die insbesondere in einer fehlenden IT-Compliance resultieren können. Wie Studien zeigen, sind KMU in Bezug auf IT-Compliance-Maßnahmen im Vergleich zu kapitalmarktorientierten Unternehmen jedoch im Rückstand [1]. Im Beitrag wird mithilfe von Experteninterviews und einer qualitativen Datenanalyse der Frage nachgegangen, welcher Status quo an Maßnahmen aktuell implementiert und wie der empfundene Compliance-Reifegrad ist. Weiterhin werden die Gründe und Motive erörtert, die zu diesem Zustand geführt haben. Letztlich sind Treiber identifiziert worden, die zu einem höheren Bewusstsein in der Zukunft führen können. Die Arbeit zeigt interessante Erkenntnisse aus der Praxis, da die Experteninterviews Einblicke in den aktuellen Status quo in Bezug auf IT-Compliance liefern.
Der Gegenstand dieser Bachelorarbeit ist die automatisierte Extraktion von Polygonzügen anhand eines Grundrissbildes. Diese Polygonzüge sollen die Räumlichkeiten wiedergeben. In dieser Bachelorarbeit wurde daher ein Algorithmus für die Grundrissbildverarbeitung mittels Python entwickelt und implementiert. Zuerst wird ein Grundrissbild bereinigt, d. h. es werden unerwünschte Bildstrukturen verwaschen. Mithilfe des Canny-Kantendetektors werden anschließend die Kanten detektiert. Danach werden die Ecken im Grundrissbild via Harris-Eckendetektor lokalisiert. Um die Ecken sinnvoll zu verbinden, wird eine abgewandelte Form des Dijkstra Algorithmus herangezogen. Die daraus gewonnen Daten dienen zur Erstellung der Polygonzüge, welche für die Simulation von pFlow benötigt werden. Der entwickelte Algorithmus eignet sich insbesondere für klare und simple Grundrissbilder.
Interpretability and uncertainty modeling are important key factors for medical applications. Moreover, data in medicine are often available as a combination of unstructured data like images and structured predictors like patient’s metadata. While deep learning models are state-of-the-art for image classification, the models are often referred to as ’black-box’, caused by the lack of interpretability. Moreover, DL models are often yielding point predictions and are too confident about the parameter estimation and outcome predictions.
On the other side with statistical regression models, it is possible to obtain interpretable predictor effects and capture parameter and model uncertainty based on the Bayesian approach. In this thesis, a publicly available melanoma dataset, consisting of skin lesions and patient’s age, is used to predict the melanoma types by using a semi-structured model, while interpretable components and model uncertainty is quantified. For Bayesian models, transformation model-based variational inference (TM-VI) method is used to determine the posterior distribution of the parameter. Several model constellations consisting of patient’s age and/or skin lesion were implemented and evaluated. Predictive performance was shown to be best by using a combined model of image and patient’s age, while providing the interpretable posterior distribution of the regression coefficient is possible. In addition, integrating uncertainty in image and tabular parts results in larger variability of the outputs corresponding to high uncertainty of the single model components.
Background:
One of the most promising health care development areas is introducing telemedicine services and creating solutions based on blockchain technology. The study of systems combining both these domains indicates the ongoing expansion of digital technologies in this market segment.
Objective:
This paper aims to review the feasibility of blockchain technology for telemedicine.
Methods:
The authors identified relevant studies via systematic searches of databases including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar. The suitability of each for inclusion in this review was assessed independently. Owing to the lack of publications, available blockchain-based tokens were discovered via conventional web search engines (Google, Yahoo, and Yandex).
Results:
Of the 40 discovered projects, only 18 met the selection criteria. The 5 most prevalent features of the available solutions (N=18) were medical data access (14/18, 78%), medical service processing (14/18, 78%), diagnostic support (10/18, 56%), payment transactions (10/18, 56%), and fundraising for telemedical instrument development (5/18, 28%).
Conclusions:
These different features (eg, medical data access, medical service processing, epidemiology reporting, diagnostic support, and treatment support) allow us to discuss the possibilities for integration of blockchain technology into telemedicine and health care on different levels. In this area, a wide range of tasks can be identified that could be accomplished based on digital technologies using blockchains.
Preliminary results of homomorphic deconvolution application to surface EMG signals during walking
(2021)
Homomorphic deconvolution is applied to sEMG signals recorded during walking. Gastrocnemius lateralis and tibialis anterior signals were acquired according to SENIAM recommendation. MUAP parameters like amplitude and scale were estimated, whilst the MUAP shape parameter was fixed. This features a useful time-frequency representation of sEMG signal. Estimation of scale MUAP parameter was verified extracting the mean frequency of filtered EMG signal, extracted from the scale parameter estimated with two different MUAP shape values.
Normal breathing during sleep is essential for people’s health and well-being. Therefore, it is crucial to diagnose apnoea events at an early stage and apply appropriate therapy. Detection of sleep apnoea is a central goal of the system design described in this article. To develop a correctly functioning system, it is first necessary to define the requirements outlined in this manuscript clearly. Furthermore, the selection of appropriate technology for the measurement of respiration is of great importance. Therefore, after performing initial literature research, we have analysed in detail three different methods and made a selection of a proper one according to determined requirements. After considering all the advantages and disadvantages of the three approaches, we decided to use the impedance measurement-based one. As a next step, an initial conceptual design of the algorithm for detecting apnoea events was created. As a result, we developed an activity diagram on which the main system components and data flows are visually represented.
Respiratory diseases are leading causes of death and disability in the world. The recent COVID-19 pandemic is also affecting the respiratory system. Detecting and diagnosing respiratory diseases requires both medical professionals and the clinical environment. Most of the techniques used up to date were also invasive or expensive.
Some research groups are developing hardware devices and techniques to make possible a non-invasive or even remote respiratory sound acquisition. These sounds are then processed and analysed for clinical, scientific, or educational purposes.
We present the literature review of non-invasive sound acquisition devices and techniques.
The results are about a huge number of digital tools, like microphones, wearables, or Internet of Thing devices, that can be used in this scope.
Some interesting applications have been found. Some devices make easier the sound acquisition in a clinic environment, but others make possible daily monitoring outside that ambient. We aim to use some of these devices and include the non-invasive recorded respiratory sounds in a Digital Twin system for personalized health.
A residual neural network was adapted and applied to the Physionet/Computing data in Cardiology Challenge 2020 to detect 24 different classes of cardiac abnormalities from 12-lead. Additive Gaussian noise, signal shifting, and the classification of signal sections of different lengths were applied to prevent the network from overfitting and facilitating generalization. Due to the use of a global pooling layer after the feature extractor, the network is independent of the signal’s length. On the hidden test set of the challenge, the model achieved a validation score of 0.656 and a full test score of 0.27, placing us 15th out of 41 officially ranked teams (Team name: UC_Lab_Kn). These results show the potential of deep neural networks for ap- plication to raw data and a complex multi-class multi-label classification problem, even if the training data is from di- verse datasets and of differing lengths.
We compared vulnerable and fixed versions of the source code of 50 different PHP open source projects based on CVE reports for SQL injection vulnerabilities. We scanned the source code with commercial and open source tools for static code analysis. Our results show that five current state-of-the-art tools have issues correctly marking vulnerable and safe code. We identify 25 code patterns that are not detected as a vulnerability by at least one of the tools and 6 code patterns that are mistakenly reported as a vulnerability that cannot be confirmed by manual code inspection. Knowledge of the patterns could help vendors of static code analysis tools, and software developers could be instructed to avoid patterns that confuse automated tools.
The evaluation of the effectiveness of different machine learning algorithms on a publicly available database of signals derived from wearable devices is presented with the goal of optimizing human activity recognition and classification. Among the wide number of body signals we choose a couple of signals, namely photoplethysmographic (optically detected subcutaneous blood volume) and tri-axis acceleration signals that are easy to be simultaneously acquired using commercial widespread devices (e.g. smartwatches) as well as custom wearable wireless devices designed for sport, healthcare, or clinical purposes. To this end, two widely used algorithms (decision tree and k-nearest neighbor) were tested, and their performance were compared to two new recent algorithms (particle Bernstein and a Monte Carlo-based regression) both in terms of accuracy and processing time. A data preprocessing phase was also considered to improve the performance of the machine learning procedures, in order to reduce the problem size and a detailed analysis of the compression strategy and results is also presented.
Good sleep is crucial for a healthy life of every person. Unfortunately, its quality often decreases with aging. A common approach to measuring the sleep characteristics is based on interviews with the subjects or letting them fill in a daily questionnaire and afterward evaluating the obtained data. However, this method has time and personal costs for the interviewer and evaluator of responses. Therefore, it would be important to execute the collection and evaluation of sleep characteristics automatically. To do that, it is necessary to investigate the level of agreement between measurements performed in a traditional way using questionnaires and measurements obtained using electronic monitoring devices. The study presented in this manuscript performs this investigation, comparing such sleep characteristics as "time going to bed", "total time in bed", "total sleep time" and "sleep efficiency". A total number of 106 night records of elderly persons (aged 65+) were analyzed. The results achieved so far reveal the fact that the degree of agreement between the two measurement methods varies substantially for different characteristics, from 31 minutes of mean difference for "time going to bed" to 77 minutes for "total sleep time". For this reason, a direct exchange of objective and subjective measuring methods is currently not possible.
Polysomnography is a gold standard for a sleep study, and it provides very accurate results, but its cost (both personnel and material) are quite high. Therefore, the development of a low-cost system for overnight breathing and heartbeat monitoring, which provides more comfort while recording the data, is a well-motivated challenge. The system proposed in this manuscript is based on the usage of resistive pressure sensors installed under the mattress. These sensors can measure slight pressure changes provoked during breathing and heartbeat. The captured signal requires advanced processing, like applying filters and amplifiers before the analog signal is ready for the next step. Then, the output signal is digitalized and further processed by an algorithm that performs a custom filtering before it can recognize breathing and heart rate in real-time. The result can be directly visualized. Furthermore, a CSV file is created containing the raw data, timestamps, and unique IDs to facilitate further processing. The achieved results are promising, and the average deviation from a reference device is about 4bpm.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
This paper presents the implementation of deep learning methods for sleep stage detection by using three signals that can be measured in a non-invasive way: heartbeat signal, respiratory signal, and movement signal. Since signals are measurements taken during the time, the problem is seen as time-series data classification. Deep learning methods are chosen to solve the problem are convolutional neural network and long-short term memory network. Input data is structured as a time-series sequence of mentioned signals that represent 30 seconds epoch, which is a standard interval for sleep analysis. The records used belong to the overall 23 subjects, which are divided into two subsets. Records from 18 subjects were used for training the data and from 5 subjects for testing the data. For detecting four sleep stages: REM (Rapid Eye Movement), Wake, Light sleep (Stage 1 and Stage 2), and Deep sleep (Stage 3 and Stage 4), the accuracy of the model is 55%, and F1 score is 44%. For five stages: REM, Stage 1, Stage 2, Deep sleep (Stage 3 and 4), and Wake, the model gives an accuracy of 40% and F1 score of 37%.
Globalization has increased the number of road trips and vehicles. The result has been an intensification of traffic accidents, which are becoming one of the most important causes of death worldwide. Traffic accidents are often due to human error, the probability of which increases when the cognitive ability of the driver decreases. Cognitive capacity is closely related to the driver’s mental state, as well as other external factors such as the CO2 concentration inside the vehicle. The objective of this work is to analyze how these elements affect driving. We have conducted an experiment with 50 drivers who have driven for 25 min using a driving simulator. These drivers completed a survey at the start and end of the experiment to obtain information about their mental state. In addition, during the test, their stress level was monitored using biometric sensors and the state of the environment (temperature, humidity and CO2 level) was recorded. The results of the experiment show that the initial level of stress and tiredness of the driver can have a strong impact on stress, driving behavior and fatigue produced by the driving test. Other elements such as sadness and the conditions of the interior of the vehicle also cause impaired driving and affect compliance with traffic regulations.
Fatigue and drowsiness are responsible for a significant percentage of road traffic accidents. There are several approaches to monitor the driver’s drowsiness, ranging from the driver’s steering behavior to analysis of the driver, e.g. eye tracking, blinking, yawning or electrocardiogram (ECG). This paper describes the development of a low-cost ECG sensor to derive heart rate variability (HRV) data for the drowsiness detection. The work includes the hardware and the software design. The hardware has been implemented on a printed circuit board (PCB) designed so that the board can be used as an extension shield for an Arduino. The PCB contains a double, inverted ECG channel including low-pass filtering and provides two analog outputs to the Arduino, that combined them and performs the analog-to-digital conversion. The digital ECG signal is transferred to an NVidia embedded PC where the processing takes place, including QRS-complex, heart rate and HRV detection as well as visualization features. The compact resulting sensor provides good results in the extraction of the main ECG parameters. The sensor is being used in a larger frame, where facial-recognition-based drowsiness detection is combined with ECG-based detection to improve the recognition rate under unfavorable light or occlusion conditions.
A significant proportion of road traffic accidents are due to inattentiveness or fatigue at the wheel. Approaches to monitoring the driver's condition range from eye tracking and driving behavior analysis to yawn and blink detection and ECG measurement. This work describes the development of a mobile system for the measurement and processing of ECG data. The aim of the signal processing is to quantify the driver’s fatigue with the heartrate variability (HRV). The work includes the hardware and software design of the sensor. First, the development of low-noise electronics including AD conversion is described. Then the software signal processing with QRS complex detection and plotting front end is explained. The resulting sensor is compact, low-cost and provides a good signal for HRV extraction.
Sleep study can be used for detection of sleep quality and in general bed behaviors. These results can helpful for regulating sleep and recognizing different sleeping disorders of human. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this work is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides, these methods not only decrease practicality due to the process of having to put them on, but they are also very expensive. The system proposed in this paper classifies respiration and body movement with only one type of sensor and also in a noninvasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed excellent results in the classification of breathing rate and body movements.
The overall goal of this work is to detect and analyze a person's movement, breathing and heart rate during sleep in a common bed overnight without any additional physical contact. The measurement is performed with the help of
sensors placed between the mattress and the frame. A two-stage pattern classification algorithm based has been implemented that applies statistics analysis to recognize the position of patients. The system is implemented in a sensors-network, hosting several nodes and communication end-points to support quick and efficient classification. The overall tests show convincing results for the position recognition and a reasonable overlap in matching.
This paper presents a bed system able to analyze a person’s movement, breathing and recognize the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the bed-frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors. First test results have indicated the potential of the proposed approach for the recognition of sleep positions with 83% of correct recognized positions.
The IETF, concerned with the evolution of the Internet architecture, nowadays also looks into industrial automation processes. The contributions of a variety of IETF activities, initiated during the last ten years, enable now the replacement of proprietary standards by an open standardized protocol stack. This stack, denoted in the following as 6TiSCH-stack, is tailored for industrial internet of things (IIoTs). The suitability of 6TiSCH-stack for Industry 4.0 is yet to explore. In this paper, we identify four challenges that, in our opinion, may delay or hinder its adoption. As a prime example of that, we focus on the initial 6TiSCHnetwork
formation, highlighting the shortcomings of the default procedure and introducing our current work for a fast and reliable formation of dense network.
We investigated 50 randomly selected buffer overflow vulnerabilities in Firefox. The source code of these vulnerabilities and the corresponding patches were manually reviewed and patterns were identified. Our main contribution are taxonomies of errors, sinks and fixes seen from a developer's point of view. The results are compared to the CWE taxonomy with an emphasis on vulnerability details. Additionally, some ideas are presented on how the taxonomy could be used to improve the software security education.
To get a better understanding of Cross Site Scripting vulnerabilities, we investigated 50 randomly selected CVE reports which are related to open source projects. The vulnerable and patched source code was manually reviewed to find out what kind of source code patterns were used. Source code pattern categories were found for sources, concatenations, sinks, html context and fixes. Our resulting categories are compared to categories from CWE. A source code sample which might have led developers to believe that the data was already sanitized is described in detail. For the different html context categories, the necessary Cross Site Scripting prevention mechanisms are described.
Smart-Future-Living-Bodensee
(2018)
Die vorliegende Arbeit untersucht, wie Tools für die Überprüfung von Quell-Code auf Konformität mit Programmierstilen, die komplexere Entwurfsmuster beinhalten, als Erweiterung des statischen CodeAnalyse-Tools Checkstyle realisiert werden können. Als Beispiel wird der Joi Programmierstil verwendet, der für diese Arbeit aus der Java Spracherweiterung Joi (Java Objects by Interfaces), die die Einhaltung einiger Entwurfsmuster, die auf die Reduzierung von Code-Abhängigkeiten zielen, unterstützt, abgeleitet wurde.
Die Arbeit stellt das Wesen und die Grundzüge der Lohnsteuer, einschließlich einem kurzen Abriß der Entwicklung des Lohnsteuerverfahrens, dar. Sie ist weder als Anleitung zur Ausfüllung eines Antrags auf Lohnsteuerjahresausgleich, noch als Nachschlagwerk gedacht. Der Leser dieser Ausarbeitung kennt die wesentlichen Grundzüge der Einkommensteuer, sowie deren besonderen Merkmale, wie z.B. der "Steuerprogression". Deshalb wurde hier auf die Darstellung der Einkommensteuer verzichtet; aus diesem Grunde wurde auch nicht die Veranlagung von Arbeitnehmern zur Einkommensteuer in die Ausarbeitung aufgenommen.
Die Firma FCT bietet industriellen Unternehmen eine Lösung im Bereich Enterprise-Content-Management und Redaktionssysteme an. Der Fokus liegt auf der medienneutralen Verwaltung der Daten im XML-Format und auf dem Publizieren dieser Daten in verschiedene Ausgabeformate wie PDF, HTML oder Online Help. Die Publikation nach PDF erfolgt meistens mit Desktop Publishing Tools wie Adobe FrameMaker, Adobe InDesign oder Microsoft Word. Immer mehr wird die Publikation nach PDF mit dem W3C Standard XSL Formatting Objects (XSL-FO)eingesetzt. Die Publikation nach PDF erfolgt dabei vollautomatisch anhand von Stylesheets. Durch die vollautomatische Publikation hatte der Redakteur bisher keine Möglichkeit manuell Seitenlayout und Seitenformatierungen anzupassen, da das Anpassen der Stylesheets spezielles programmiertechnisches Know-How voraussetzt. Im Rahmen dieser Diplomarbeit wurde eine Entwicklungsumgebung konzipiert und implementiert, die es Redakteuren ermöglicht, Seitenlayout und Seitenformatierung komfortabel über eine grafische Oberfläche festzulegen. Da hierbei unterschiedliche Dokumententypen und unterschiedliche Kunden berücksichtigt werden müssen, verwendet die Anwendung ein Projektansatz um die unterschiedlichen Stylesheets, Konfigurationen und Kunden zu organisieren. Da bei unterschiedlichen Kunden verschiedene FO-Prozessoren wie Antenna House XSL Formatter, RenderX XEP oder Apache FOP zum Einsatz kommen, war es ein Schwerpunkt dieser Arbeit, die Unterschiede dieser Prozessoren zu analysieren und die Entwicklungsumgebung prozessorunabhängig aufzusetzen. Eine Vorschau zeigt dem Redakteur, wie sich die verschiedenen Konfigurationen auf das PDF-Dokument auswirken, um gegebenenfalls weitere Änderungen am Seitenlayout bzw. Seitenformatierungen vorzunehmen.
Anbindung eines PPC405 embedded CPU Core an ein MPC860-System unter dem Echtzeitbetriebssystem OSE
(2006)
Die Diplomarbeit verfolgt das Ziel, die softwareseitige Anbindung eines PPC405-Systems an das Gesamtsystem einer digitalen Funkgeräteplattform herzustellen. Über eine konzipierte Implementierung, die nach dem Einschalten des Funkgeräts gestartet wird, erfolgt die Übertragung des Betriebssystems in den zugehörigen Arbeitsspeicher des PPC405-Systems. Nach Abschluss der Initialisierungsphase kommunizieren die Anwendungsprozesse auf den beteiligten Systemen über eine transparente Erweiterung des Betriebssystems mit der jeweiligen Gegenseite. Als Übertragungsmedium für die genannte Betriebssystemerweiterung wird ein zwischen den Systemen angesiedelter Speicher genutzt, für dessen koordinierte Zugriffe eine im Rahmen der Diplomarbeit entwickelte Treiberkomponente sorgt. Durch die Anbindung des PPC405-Systems wird eine Leistungssteigerung des Gesamtsystems erwartet. Auf der Basis von Messungen wurde die Performance des somit erhaltenen Multiprozessorsystems bestimmt. Aus den Ergebnissen wurden geeignete Möglichkeiten zur Optimierung erarbeitet und umgesetzt.
Die Zielsetzung dieser Arbeit ist die Entwicklung der Serverdienste einer Client/Server-Software für die computergestützte Telefonie am Arbeitsplatz. Die Software ermöglicht die Steuerung und Statusüberwachung von Telefonapparaten mit dem Ziel, die Benutzung ergonomischer zu gestalten und das zugrunde liegende Telekommunikationssystem stärker in die Informationstechnik zu integrieren. Die Software soll mit der Telekommunikationsanlage Meridian I von Nortel zusammenarbeiten, um die Manipulation der angeschlossenen Telefonapparate zu ermöglichen. Beim Softwareentwurf ist für die Zukunft die Unterstützung weiterer Telekommunikationsanlagen zu berücksichtigen. Zudem soll ein API definiert werden, welches die Implementierung eines Clients in Form eines HTTP-Dienstes für die Nutzung über einen Web-Browser ermöglicht. Ebenso soll der Weg für eine in Zukunft zu entwickelnde dedizierte Client-Software bereitet werden. Für die Umsetzung der Projektziele wurde ein komponentenorientiertes Middleware-Konzept auf Basis des Java Telephony Application Programming Interface (JTAPI) verwirklicht. Dafür wurde eine JTAPI-konforme Provider-Implementierung realisiert, die das zugehörige Zustands- und Objektmodell umsetzt. Für die Kommunikation mit der Telekommunikationsanlage wurde eine Treiberkomponente entwickelt, die das proprietäre Protokoll des CTI-Links implementiert. Schließlich wurde ein einheitliches, RMI-basiertes API spezifiziert, das für die Entwicklung der Client-Software in Form eines HTTP-Dienstes oder einer selbständigen, fensterbasierten Anwendung eingesetzt werden kann. Die komponentenorientierte Gesamtarchitektur ermöglicht darüber hinaus die Entwicklung weiterführender CTI-Dienste.
Selbstorganisierende Karten sind neuronale Netze, die imstande sind, Daten zu klassifizieren und zu reduzieren. Aus diesem Grund eignen sie sich sehr gut fuer die Steuerung von Robotern, da sie deren Sensoreingangswerte klassifizieren und daraus auf eine Reaktion schließen koennen. Die Architektur und Funktionsweise dieser neuronalen Netze sind der des menschlichen Kortex kuenstlich nachgebildet. Im Rahmen dieser Diplomarbeit wurde ein Java-Framework namens JFSOM implementiert, welches nach dem System einer selbstorganisierenden Karte Datenmengen klassifizieren kann. Das Framework ist so entworfen, dass sowohl Eingabedaten als auch Ausgabedaten trainiert werden koennen, um es auch als sensormotorische Karte nutzbarzu machen. JFSOM wurde verwendet, um den Miniaturroboter Khepera nach bestimmten Verhaltensweisen zu steuern. Als Verhaltensweisen wurden eine Hindernisvermeidung, eine Wandverfolgung, eine Korridorverfolgung und eine Objektverfolgung realisiert. Die Wandverfolgung laesst den Roboter aus jedem beliebigen azyklischen Labyrinth herausfinden.
Zur Verringerung der Kosten und des Aufwands zur Installation, Update und Wartung von Workstations in einem industriellen Umfeld, sollte ein System zur zentralen, hardwareunabhängigen und vollautomatischen Installation dieser Workstations eingeführt werden. Hierzu mussten zuerst einmal die Möglichkeiten für eine vollautomatische Installation der verschiedenen Betriebssysteme und Anwendungen betrachtet werden. Nach dem Aufbau der Hardware folgte daraufhin die Installation des Deployment Systems der Firma OnTechnology (OnCommand). Im Anschluss daran wurden die Skripte für die Betriebssystem- und Anwendungsinstallation erstellt. Diese Skripte wurden anschließend zur besseren Handhabung zu Profilen zusammengefasst. Im nächsten Schritt wurden bestehende Clients in das System integriert. Daraufhin wurde das Sicherheitskonzept des Systems betrachtet, mit dem die Möglichkeit besteht bestimmten Benutzern nur bestimmte Rechte zu vergeben. In weiteren Teilen der Diplomarbeit werden die bisherigen Probleme bei der Firma und das erhoffte Ziel, die Möglichkeiten des Systems, sowie die Probleme bei der Umsetzung beziehungsweise des Systems, dargestellt und im Fazit zusammengefasst.
Die vorliegende Arbeit soll die Möglichkeiten von XML und den dazugehörigen Technologien bei der Entwicklung eines komplexen Softwaresystems und dem damit verbundenen Datenaustausch aufzeigen. Dafür soll die Leistungsfähigkeit und Eignung oder ggf. Nichteignung der XML-Technologie durch Entwurf, Aufbau und Test eines Prototyps, durch XML-konforme Ein- und Ausgabe sowie durch Daten- Aufbereitung und -auswertungen nachgewiesen werden. Daten unterschiedlicher Datenbestände werden ins XML-Format transformiert und in eine zentrale Datenbank gespeichert. Diese sollen mittels XML für alle Fremddatensysteme bereitgestellt sowie in HTML- und PDF-Formate transformiert werden.
This thesis deals with background, theory, design, layout and experimental test results of an analogue CMOS VLSI current-mode analog-to-digital converter. This system supports a project, whose goal it is to build a biologically relevant model of synaptic plasticity, named the Artificial Synapse. A critical part of the design, which is based on analogue CMOS VLSI circuits, is the ability to activate a discrete number of channels by sampling an analogue signal. Since currents are the signal of interest and transistors are biased in weak inversion (subthreshold regime), the system requires a current mode A/D circuit that it can operate at ultra-low power and current levels. To meet this need, two new innovative A/D converter approaches are proposed to replace the system’s previous A/D converter design which suffered from a non-linear resolution, uncoded output code and heavy bit oscillations. The initial technical requirements and key criteria for the new converter comprise a resolution of one nano ampere, an input current range between 0 – 100nA, conversion frequencies of up to 5kHz, and a power supply voltage of less than 1.5V. Temperature range, space occupation and power dissipation aspects were not specified due to the early stage of the related Artificial Synapse project. The novel converters both produce seven bit thermometer codes, their functional principle can be best described as current mode flash analog-to-digital converters (ADCs). Due to the fact that the input signal is in the area of a subthreshold current, it is selfevident that the A/D converter design should operate at a subthreshold realm. To support low power operation, clocks or high currents could not be used and were excluded from the design from the very start. To encode the thermometer code into standard binary code, a seven-to-three encoder was designed and integrated on the chip. In October 2003, the design was submitted for production to the MOSIS circuit fabrication service. The AMI Semiconductor 1.5 micron ABN CMOS process was chosen to manufacture the chip. When it was returned in January 2004, simulation results showed that both new A/D converter approaches accomplished excellent results which were expected from SPICE simulation results. With the new chip installed, it became possible to resolve input currents as small as one nano ampere and achieve conversion frequencies of up to 5kHz. The circuits also both meet the requirements which were set at the beginning of the project to operate at a power supply voltage of less than 1.5V, processing input currents in the range between 0 – 100nA. A prototype printed circuit board (PCB) was developed, produced and employed for experiments with the chip. The major application of this test-bed is the ability to generate and measure extremely low currents with high precision. This enables the monitoring of the very small currents that are processed by the chip.
Web services are, due to the excellent tool support, simple to provide and use in trivial cases. But their use in non-trivial Web service-based systems like I3M poses new difficulties and problems. I3M is an instant messaging and chat system with distributed and local components collaborating via Web services. One difficulty is to make a series of related Web service invocations in a stateful session. A problem is the performance of collaborating collocated, service-oriented components of a system due to the high Web service invocation overheaed as is shown by measurements. Solutions to both the difficulty and the problem are proposed.
Logopädische Lernsoftware
(2003)
In den letzen Jahren konnte ein wachsendes Interesse an Lernsoftware im logopä-dischen Einsatzbereich verzeichnet werden. Dieses Interesse zeigte sich nicht nur auf Seite der logopädischen Fachpraxen sondern auch in den Grundschulen. Auf Grund dessen ist die Lernsoftware auf dem besten Wege, sich neben den traditionellen Lern- und Übungsmaterialien am Markt zu etablieren. Auf Grund der Vielfalt an Sprachstörungen wird ein System benötigt, das indivi-duell, je nach Bedürfnis des Klienten, konfiguriert werden kann. Die vorliegende Arbeit beschäftigt sich mit dem Entwurf und der Weiterentwick-lung der logopädischen Lernsoftware Detektiv Langohr, damit dieses Produkt den Anforderungen und Wünschen des Klientel so gerecht wie möglich wird. Auf Basis einer durchgeführten Marktanalyse wurden konkrete Anforderungen an ein solches System spezifiziert und im Anschluss in ein Projekt umgesetzt. Um dem Leser einen besseren Einblick in die Welt der Logopädie verschaffen zu können, wurde eine allgemeine Einführung in die Sprachtherapie dem Analyse- und Um-setzungsteil vorangestellt.
This work treats with the segmentation of 2D environment Laser data, captured by an Autonomous Mobile Indoor Robot. It is part of the data processing, which is necessary to navigate a mobile robot error free in its environment. The whole process can generally be described by data capturing, data processing and navigation. In this project the data processing deals with data, captured by a Laser-Sensor, which provides two dimensional data by a series of distance measurements i.e. point-measurements of the environment. These point series have to be filtered and processed into a more convenient representation to provide a virtual environment map, which can be used of the robot for an error free navigation. This project provides different solutions of the same problem: the conversion from distance points to model segments which should represent the real world environment as close as possible. The advantages and disadvantages of each of the different Segmentation-Algorithms will be shown as well as a comparison taking into account the Computational Time and the Robustness of the results.
Das historisch gewachsene System für die Erstellung, Koordinierung und Auskunft der Lehrveranstaltungspläne (LVP) soll durch ein neues System ersetzt werden. Diese Diplomarbeit befasst sich mit der Konzeption und der Implementierung einer neuen grafischen Benutzeroberfläche und der Migration auf eine SQL basierte Datenbank für das komplette Management der Lehrveranstaltungspläne der FH Konstanz. Wie die Stundenpläne an den Schulen müssen auch die Lehrveranstaltungspläne an der Fachhochschule in jedem Semester entworfen, zu Papier gebracht, vervielfältigt und verteilt werden. An der FH Konstanz wird die heikle Aufgabe des Entwerfens von den LVP- Beauftragten der Studiengänge erledigt, denn sie können die vielen Randbedingungen besser überschauen und das Ergebnis auch rechtfertigen. Für die Routinearbeiten Auskunft und Drucken gab es bisher das LVP- Programm als ein spezielles Informationssystem. Auch wenn sich das bisherige System bewährt hat, blieben doch einige Wünsche der Planer offen. Da das LVP- System über mehrere Jahre gewachsen war, ist man an einige Eigenheiten gebunden, die es zu eliminieren gilt. Auch neue Technologien eröffnen einige interessante Möglichkeiten, die früher noch nicht so einfach, oder gar nicht zu implementieren waren. Ziel dieser Diplomarbeit ist eine komplette Neuentwicklung des gesamten Systems unter Verwendung aktueller Technologien: das LVP³- System.
Im Rahmen dieser Diplomarbeit wird eine horizontale Baumkomponente als JavaBean erstellt. Die Baumkomponente soll als Truppenbaum in ein bestehendes Führungs-Informationssystem implementiert werden. Dazu ist die Verwendung des SVG (XML) Grafikformates zur Darstellung der Symbole einzelner Knoten erforderlich. Weiterhin wird die Interaktion von Java-Komponenten mit Windows COM und DCOM untersucht. Es werden mehrere unterschiedliche Java-COM-Bridges getestet. In der vorliegenden Arbeit wird zuerst auf die Grundlagen eingegangen, indem das XML und SVG Format vorgestellt wird und die Grundlagen von JavaBeans sowie die benutzten Bibliotheken erläutert werden. Anschließend wird die Entwicklung der Komponente mit Pflichtenheft, Architektur und Implementierung dargestellt. Abschließend werden die Java-COM-Bridges beschrieben.
Die Arbeit befasst sich mit dem J2EE Framework Jakarta Struts. Hauptziel ist es, den Einsatz von Struts in der ZKB zu prüfen. Es soll festgestellt werden, ob Struts in Zukunft für die Entwicklung grösserer Web-Applikationen in der ZKB eingesetzt werden kann. Dazu wird eine bereits existierende ASP Web-Applikation zuerst zu einer JSP-Applikation (Model 1) und anschliessend zu einer Struts-Applikation (Model 2) portiert. Danach werden die beiden Versionen bzgl. Entwicklungsaufwand, Funktionsumfang, Performance und Wartbarkeit miteinander verglichen. Darüber hinaus werden Fähigkeiten des Struts Frameworks beleuchtet, die Architektur des Frameworks beschrieben und überprüft, inwiefern das Framework den Entwickler entlasten kann. Entwickler ohne Erfahrung mit Struts finden hier ausserdem eine verständliche Einführung an einem überschaubaren Beispiel. Nach der Einleitung in Kapitel 1 werden im zweiten Kapitel die Struts zu Grunde liegenden Technologien der Java 2 Plattform Enterprise Edition (J2EE) von Sun beschrieben. Im dritten Kapitel wird detailliert auf Struts eingegangen. Um dem Leser den Einstieg in Struts zu erleichtern, wird vor der Beschreibung der Struts Komponenten die Architektur und der Programmablauf erläutert. Eine Anleitung zum Erstellen einer kleinen Struts Applikation erklärt Struts an einem praktischen Beispiel. Vergleichbare Frameworks werden am Ende des Kapitels vorgestellt. Im vierten Kapitel erläutere ich die Entwicklung der von mir mit Struts erstellten Web-Applikation. Die beiden letzten Kapitel enthalten die Erkenntnisse aus meiner Arbeit mit Struts und versuchen eine Entscheidungsgrundlage für oder gegen den Einsatz des Frameworks zu liefern.
This thesis investigates methods for the recognition of facial expressions using support vector machines. Rather than trying to recognize facial actions in the face such as raised eyebrow, mouth open and frowns. These facial actions are described in the Facial Action Coding System (FACS) and are essential facial components, which can be combined to form facial expressions. We perform independent recognition of 6 upper and 10 lower action units in the face, which may occur either individually or in combination. Based on a feature extraction from grey-level values, the system is expected to recognize under real-time conditions. Results are presented with different image resolutions, SVM kernels and variations of low-level features.
Die zunehmende Internationalisierung der Märkte, das wachsende, immer differenziertere Produktangebot und die hohe technische Innovationsgeschwindigkeit führen zu immer härteren Wettbewerbsbedingungen auf dem Markt. Diese Situation zwingt die Unternehmen nicht nur zu kontinuierlichen Anstrengungen, um ihre Produktivität und Qualität zu steigern, sondern es stehen auch immer geringere Mittel für die Realisierung von Produktions- und/oder Messeinheiten innerhalb des Produktionsprozesses zur Verfügung. Als Folge dessen werden Entwickler mit folgenden Grundforderungen konfrontiert: · Abstimmung der Architektur auf vorhandene und/oder gängige Infrastrukturen · Reduzierung des Entwicklungsaufwandes durch Modularisierung des Systemaufbaues · Reduzierung der Wartungs- und Administrationskosten durch einfache Handhabbarkeit · Maximierung der Betriebssicherheit und Minimierung der Ausfallzeiten · Einfache Erweiterbarkeit · Hohe Wiederverwendbarkeit Ein Resümee von Softwareprojekten über die letzten Jahre zeigt, dass sich der Rahmen für Softwareentwicklung insgesamt geändert hat. Softwareprojekte sind heute mehrschichtige, verteilte (ggf. auch komponentenbasierte) Anwendungen mit gestiegenen Anforderungen an Funktionalität, Qualität und Flexibilität. Leider beinhalten die Architekturen und Konzepte der ‚Verteilten Systeme' Schwächen, diese für verteilte Mess- und Steuerungssysteme direkt umzusetzen. Ziel dieser Arbeit ist es, die Schwächen vorhandener Konzepte aufzuzeigen und eine Architektur vorzustellen, die den Entwickler unterstützt, verteilte Mess- und Steuerungssysteme bis hin zu Prozessleitsystemen unter dem Betriebssystem Windows zu entwickeln.
Tauchsimulation
(2003)
Im 1.Kapitel werden die historischen Aspekte des Tauchens und der Tauchphysik beschrieben. Anhand von physikalischen Gesetzen, mathematischen Formeln und empirisch ermittelten Werten werden im 2. Kapitel die nötigen Grundlagen für das Verständnis zur Berechnung eines Tauchgangs vermittelt. Das 3.Kapitel behandelt verschiedene auf dem Markt befindliche Tauchsimulationen, zeigt deren Funktionsumfang sowie deren Vor- und Nachteile. Die erstellte Tauchsimulation wird im 4. Kapitel vorgestellt. Dabei wird auch auf verschiedene Simulationsläufe eingegangen. Zum Abschluß wird ein Ausblick auf aktuelle Entwicklungstendenzen gegeben.
The target of this thesis is the introduction of a client management system (CMS) at Haaland Internet Productions (HiP), a web design and hosting company in Burbank, California, USA. The company needs a system to track orders and improve workflow. HiP needs a system which not only tracks orders, but also stores all client information in a database. This client information can be used for a variety of marketing and contact reasons. It is an important and integral part of HiP's client relationship management (CRM). The lack of a cohesive CMS at HiP caused many fundamental business problems, such as lost orders, missed billing statements, and over/under billing. The research done during the investigation and analysis of the company and their needs should lead to a global system which totally fulfils the needs of HiP. This global system could be in the form of an off-the-shelf product with some customizations, or a completely new, in-house system. Either solution will have respective pros and cons; the goal is to reach a decision that best fits HiP's needs and situation. The following is a concise version of the project. Particular emphasis is placed upon the single steps which made up the decision process, as well as the practiced techniques, methods, and their applications.