A tandem repeat is a sequence of adjacent repetitions of a nucleotide patternsignature, called its motif, in a DNA sequence. The repetitions may either be exact or approximate copies of the motif. A minisatellite is a tandem repeat whose motif is of moderate length. One approach to searching for minisatellites assumes prior knowledge about the motif. This approach limits the search for minisatellites to specified motifs. An alternative approach tries to identify signatures autonomously from within a DNA sequence. Several different algorithms that use this approach have been developed. Since they do not use pre-specified motifs, and since a degree of approximation is tolerated, there may be ambiguity about where minisatellites start and end in a given DNA sequence. Various experiments were conducted on four well-known software packages to investigate this conjecture. The software packages were executed on the same data and their respective output was compared. The study found that the selected computer algorithms did not report the same outputs. The lack of precise definitions of properties of such patterns may explain these differences. The difference in definitions relate to the nature and extent of approximation to be tolerated in the patterns during the search. This problem could potentially be overcome by agreeing on how to specify acceptable approximations when searching for minisatellites. Some of these packages are implemented as Academic/Research Software (ARS). Noting that ARS has a reputation of being difficult to use, this study also investigated the usability of these ARS implementations. It relied on literature that offers usability evaluation methods. Potential problems that are likely to affect the general usability of the systems were identified. These problems relate inter alia, to visibility, consistency and efficiency of use. Furthermore, usability guidelines in the literature were followed to modify the user interface of one of the implementations. A sample of users evaluated the before- and after versions of this user interface. Their feedback suggests that the usability guidelines were indeed effective in enhancing the user interface. / Dissertation (MSc)--University of Pretoria, 2013. / gm2014 / Computer Science / unrestricted

One way that examinees can gain an unfair advantage on a test is by having prior access to the test questions and their answers, known as preknowledge. Determining which examinees had preknowledge can be a difficult task. Sometimes, the compromised test content that examinees use to get preknowledge has mistakes in the answer key. Examinees who had preknowledge can be identified by determining whether they used this flawed answer key. This research consisted of three papers aimed at helping testing programs detect examinees who used a flawed answer key. The first paper developed three methods for detecting examinees who used a flawed answer key. These methods were applied to a real data set with a flawed answer key for which 37 of the 65 answers were incorrect. One requirement for these three methods was that the flawed answer key had to be known. The second paper studied the problem of estimating an unknown flawed answer key. Four methods of estimating the unknown flawed key were developed and applied to real and simulated data. Two of the methods had promising results. The methods of estimating an unknown flawed answer key required comparing examinees’ response patterns, which was a time-consuming process. In the third paper, OpenMP and OpenACC were used to parallelize this process, which allowed for larger data sets to be analyzed in less time.

In this paper I assess the potential for improvement in the documentation of metal detecting in the Swedish contract archaeology. I then investigate how such an improvement could be achieved. The study consists of three parts. I begin by defining what makes up high-quality documentation of metal detecting. I then use this definition to develop criteria for an assessment system. In the second part I use this assessment system for a quantitative analysis of archaeological archive reports from four of the largest contract-archaeology organizations in the Lake Mälaren area. Finally I report on interviews I have made with representatives from two of the studied organizations to seek possible explanations for the results of my analysis. My study confirms that there is considerable room for improvement in the analyzed archive reports, and sheds light on what parts of the documentation show frequent flaws. The results suggest that information specific to metal detecting is the most lacking, such as the selection of metal indications and fieldwork conditions. But there are also considerable flaws in more elementary information about surveys, which would probably never be accepted if it were a question of more traditional fieldwork methods.

<p>To test if a host contains any known security flaws over a network connection a Vulnerability Assessment (VA) could be made. This thesis describes different techniques used by VA tools over a network connection to detect known security flaws. To decrease the risk of flaws not being detected, several VA tools could be used.</p><p>There is no common way of merging information from different VA tools. Therefore the Vulnerability Assessment Information Handler (VAIH) has been developed. The VAIH system consists of three parts. First, a intermediate language format defined in XML. Second, modules that converts the output of VA tools to the intermediate language format. Third, a program for reading and displaying the intermediate language format.</p><p>The VAIH system makes it possible to merge the results from vulnerability assessment tools into one file that can be displayed and edited through a GUI.</p>

Cryptographic hardware has found many uses in many ubiquitous and pervasive security devices with a small form factor, e.g. SIM cards, smart cards, electronic security tokens, and soon even RFIDs. With applications in banking, telecommunication, healthcare, e-commerce and entertainment, these devices use cryptography to provide security services like authentication, identification and confidentiality to the user. However, the widespread adoption of these devices into the mass market, and the lack of a physical security perimeter have increased the risk of theft, reverse engineering, and cloning. Despite the use of strong cryptographic algorithms, these devices often succumb to powerful side-channel attacks. These attacks provide a motivated third party with access to the inner workings of the device and therefore the opportunity to circumvent the protection of the cryptographic envelope. Apart from passive side-channel analysis, which has been the subject of intense research for over a decade, active tampering attacks like fault analysis have recently gained increased attention from the academic and industrial research community. In this dissertation we address the question of how to protect cryptographic devices against this kind of attacks. More specifically, we focus our attention on public key algorithms like elliptic curve cryptography and their underlying arithmetic structure. In our research we address challenges such as the cost of implementation, the level of protection, and the error model in an adversarial situation. The approaches that we investigated all apply concepts from coding theory, in particular the theory of cyclic codes. This seems intuitive, since both public key cryptography and cyclic codes share finite field arithmetic as a common foundation. The major contributions of our research are (a) a generalization of cyclic codes that allow embedding of finite fields into redundant rings under a ring homomorphism, (b) a new family of non-linear arithmetic residue codes with very high error detection probability, (c) a set of new low-cost arithmetic primitives for optimal extension field arithmetic based on robust codes, and (d) design techniques for tamper resilient finite state machines.

Detecting unusual movement (falls) for elderly people in enclosed environments is receiving increasing attention and is likely to have massive potential social and economic impact. In this thesis, new intelligent computer vision processing based techniques are proposed to detect falls in indoor environments for senior citizens living independently, such as in intelligent homes. Different types of features extracted from video-camera recordings are exploited together with both background subtraction analysis and machine learning techniques. Initially, an improved background subtraction method is used to extract the region of a person in the recording of a room environment. A selective updating technique is introduced for adapting the change of the background model to ensure that the human body region will not be absorbed into the background model when it is static for prolonged periods of time. Since two-dimensional features can generate false alarms and are not invariant to different directions, more robust three-dimensional features are next extracted from a three-dimensional person representation formed from video-camera measurements of multiple calibrated video-cameras. The extracted three-dimensional features are applied to construct a single Gaussian model using the maximum likelihood technique. This can be used to distinguish falls from non-fall activity by comparing the model output with a single. In the final works, new fall detection schemes which use only one uncalibrated video-camera are tested in a real elderly person s home environment. These approaches are based on two-dimensional features which describe different human body posture. The extracted features are applied to construct a supervised method for posture classification for abnormal posture detection. Certain rules which are set according to the characteristics of fall activities are lastly used to build a robust fall detection model.

<p>Many traffic accidents are caused by driver unawareness. This includes fatigue, drowsiness and distraction. In this thesis two systems are described that could be used to decrease the number of accidents. In the first part of this thesis a system using long-term information to warn drivers suffering from fatigue is developed. Three different versions with different criteria are evaluated. The systems are shown to handle more then 60% of the cases correctly.</p><p>The second part of this thesis examines the possibilities of developing a warning system based on the predicted time-to-lane crossing, TLC. A basic TLC model is implemented and evaluated. For short time periods before lane crossing this may offer adequate accuracy. However the accuracy is not good enough for the model to be used in a TLC based warning system to warn the driver of imminent lane departure.</p>

<p>Prostate cancer is the most common type of cancer in men in Europe and the USA. Some prostate tumours are regarded as stiffer than the surrounding normal tissue, and therefore it is of interest to be able to reliably measure prostate tissue stiffness. The methods presently used to detect prostate cancer are inexact, and new techniques are needed. In this licentiate thesis resonance sensor technology, with its ability to measure tissue stiffness, was applied to normal and cancerous prostate tissue.</p><p>A piezoelectric transducer element in a feedback system can be set to vibrate at its resonance frequency. When the sensor element contacts an object a change in the resonance frequency is observed, and this feature has been utilized in sensor systems to describe physical properties of different objects. For medical applications it has been used to measure stiffness variations due to various pathophysiological conditions.</p><p>An impression-controlled resonance sensor system was used to quantify stiffness in human prostate tissue in vitro using a combination of frequency change and force measurements. Measurements on prostate tissue showed statistically significant (p < 0.001) and reproducible differences between normal healthy tissue and tumour tissue when using a multivariate parameter analysis. Measured stiffness varied in both the normal tissue and tumour tissue group. One source of variation was assumed to be related to differences in tissue composition. Other sources of error could be uneven surfaces, different levels of dehydration of the prostates, and actual differences between patients.</p><p>The prostate specimens were also subjected to morphometric measurements, and the sensor parameter was compared with the morphology of the tissue with linear regression. In the probe impression interval 0.5–1.7 mm, the maximum coefficient of determination was R2 ≥ 0.60 (p < 0.05, n = 75). An increase in the proportion of prostate stones (corpora amylacea), stroma, or cancer in relation to healthy glandular tissue increased the measured stiffness. Cancer and stroma had the greatest effect on the measured stiffness. The deeper the sensor was pressed, the greater, i.e., deeper, volume it sensed.</p><p>It is concluded that prostate cancer increases the measured stiffness as compared with healthy glandular tissue, but areas with predominantly stroma or many stones could be more difficult to differentiate from cancer. Furthermore, the results of this study indicated that the resonance sensor could be used to detect stiffness variations in human prostate tissue in vitro, and especially due to prostate cancer. This is promising for the development of a future diagnostic tool for prostate cancer.</p>

Many traffic accidents are caused by driver unawareness. This includes fatigue, drowsiness and distraction. In this thesis two systems are described that could be used to decrease the number of accidents. In the first part of this thesis a system using long-term information to warn drivers suffering from fatigue is developed. Three different versions with different criteria are evaluated. The systems are shown to handle more then 60% of the cases correctly. The second part of this thesis examines the possibilities of developing a warning system based on the predicted time-to-lane crossing, TLC. A basic TLC model is implemented and evaluated. For short time periods before lane crossing this may offer adequate accuracy. However the accuracy is not good enough for the model to be used in a TLC based warning system to warn the driver of imminent lane departure.

Utilizing the bulk and surface micromachining technologies, this thesis designed and fabricated a piezoresistive pressure microsensor for developing an in-vivo and real-time biomedical detection microsystem to monitor the uric pressure in patients¡¦ bladder. In this study, the main processing steps include the implantation of a moderate boron ion concentration into the N-epitaxial silicon layer to form the piezoresistors, anisotropic etching the backside silicon substrate to create a cavity by 30% KOH solution in 80¢XC temperature, and anodic bonding of the silicon based pressure microsensor and the hole-drilled glass sustain. To obtain the optimum design specification of the piezoresistive pressure microsensor, this study compared the characterization of the four types of devices with three different pressure sensing area (As) and two different length/width ratios (L/W) of the N-epitaxial piezoresistors. Based on the measurement results, the highest sensitivity (0.0076mV/(V*kgf/cm2) can be achieved as the As and the L/W ratio are equal to 1050 ¡Ñ 1050 £gm2 and 90/9 £gm/£gm, respectively. Such sensitivity is suitable for the application of bladder pressure detection microsystem. A very high sensing linearity (99.6%) can also be demonstrated in this research and this value approach to that of the commercial pressure sensor. On the other hand, through cooperation with another laboratory, this work has established a prototype of the uric pressure detecting microsystem by assembled with the piezoresistive pressure microsensor, a control ASIC and a radio-frequency (RF) module.