>Magister Scientiae - MSc / The Physics Department at the University of the Western Cape and the Environmental Physics group at iThemba labs have been conducting radiometric studies on both land and water. In this study a 7.5 cm X 7.5 cm NaI (Tl) detector was used to study activity concentrations of primordial radionuclides in soil and sand samples. The detector and the sample were placed inside a lead castle to reduce background in the laboratory from the surroundings such as the wall and the floor. The samples were placed inside a 1 L Marinelli beaker which surrounds the detector for better relative efficiency as almost the whole sample is exposed to the detector. Additional lead bricks were placed below the detector to further reduce the background by 20%. The NaI detector is known to be prone to spectral drift caused by temperature differences inside and around the detector. The spectral drift was investigated by using a ¹³⁷Cs source to monitor the movements in the 662 keV peak. The maximum centroid shift was about 4 keV (for a period of 24 hours) which is enough to cause disturbances in spectral fitting. There was no correlation between the centroid shift and small room temperature fluctuations of 1.56 ºC. A Full Spectrum Analysis (FSA) method was used to extract the activity concentrations of ²³⁸U, ²³²Th and ⁴⁰K from the measured data. The FSA method is different from the usual Windows Analysis (WA) as it uses the whole spectrum instead of only putting a ‘window’ around the region of interest to measure the counts around a certain energy peak. The FSA method uses standard spectra corresponding to the radionuclides being investigated, and is expected to have an advantage when low-activity samples are measured. The standard spectra are multiplied by the activity concentrations and then added to fit the measured spectrum. Accurate concentrations are then extracted using a chi-squared (χ²) minimization procedure. Eight samples were measured in the laboratory using the NaI detector and analyzed using the FSA method. The samples were measured for about 24 hours for good statistics. Microsoft Excel and MATLAB were used to calculate the activity concentrations. The ²³⁸U activity concentration values varied from 14 ± 1 Bq/kg (iThemba soil, HS6) to 256 ± 10 Bq/kg (Kloof sample). The ²³²Th activity concentration values varied from 7 ± 1 Bq/kg (Anstip beach sand) to 53 ± 3 Bq/kg (Rawsonville soil #B31). The ⁴⁰K activity concentration values varied from 60 ± 20 Bq/kg (iThemba soil, HS6) to 190 ± 20 Bq/kg (Kloof sample). The χ² values also varied from sample to sample with the lowest being 12 (Anstip beach sand) and the highest (for samples without contamination of anthropogenic nuclei) being 357 (Rawsonville soil #B28). A high χ² value usually represents incomplete gain drift corrections, improper set of fitting functions, proper inclusion of coincidence summing or the presence of anthropogenic (man made) radionuclei in the source [Hen03]. Activity concentrations of ⁴⁰K, ²³²Th and ²³⁸U were measured at four stationary points on the Kloof mine dump. The fifth stationary point was located on the Southdeep mine dump. These measurements were analysed using the FSA method and fitting by "eye" the standard spectra to the measured spectra using Microsoft Excel. These values were then compared to values obtained using an automated minimization procedure in MATLAB. There was a good correlation between these results except for ²³²Th which had higher concentrations when MATLAB was used, where 16 Bq/kg was the average value in Excel and 24 Bq/kg was the average value in MATLAB.

Táto práca sa zaoberá redukciou veľkosti tzv. čítačových automatov. Čítačové automaty rozširujú klasické konečné automaty o čítače s obmedzeným rozsahom hodnôt. Umožňujú tým efektívne spracovať napr. regulárne výrazy s opakovaním: a{5,10}. V tejto práci sa zaoberáme reláciou simulácie v čítačových automatoch, pomocou ktorej sme schopní zredukovať ich veľkosť. Opierame sa pritom o klasickú simuláciu v konečných automatoch, ktorú netriviálnym spôsobom rozširujeme na čítačové automaty. Kľúčovým rozdielom je nutnosť simulovať okrem stavov taktiež čítače. Za týmto účelom zavádzame nový koncept parametrizovanej relácie simulácie, a navrhujeme metódy výpočtu tejto relácie a redukcie veľkosti čítačových automatov pomocou nej. Navrhnuté metódy sú tiež implementované a je vyhodnotená ich efektivita.

Witchweeds and broomrapes are root parasitic weeds that represent one of the main threats to global food security. By drastically reducing host crops’ yield, the parasites are often responsible for enormous economic losses estimated in billions of dollars annually. Parasitic plants rely on a chemical cue in the rhizosphere, indicating the presence of a host plant in proximity. Using this host dependency, research in parasitic plants focuses on understanding the necessary triggers for parasitic seeds germination, to either reduce their germination in presence of crops or provoke germination without hosts (i.e. suicidal germination). For this purpose, a number of synthetic analogs and inhibitors have been developed and their biological activities studied on parasitic plants around the world using various protocols. Current studies are using germination-based bioassays, where pre-conditioned parasitic seeds are placed in the presence of a chemical or plant root exudates, from which the germination ratio is assessed. Although these protocols are very sensitive at the chemical level, the germination rate recording is time consuming, represents a challenging task for researchers, and could easily be sped up leveraging automated seeds detection algorithms. In order to accelerate such protocols, we propose an automatic seed censing tool using computer vision latest development. We use a deep learning approach for object detection with the algorithm Faster R-CNN to count and discriminate germinated from non-germinated seeds. Our method has shown an accuracy of 95% in counting seeds on completely new images, and reduces the counting time by a significant margin, from 5 min to a fraction of second per image. We believe our proposed software 5 “SeedQuant” will be of great help for lab bioassays to perform large scale chemicals screening for parasitic seeds applications.

This effort deals with the problem of effective counting of people in the room. Although more companies deal with this problem at present, but their systems are very expensive. For this reason I strive to find a cheaper solution for counting people using active infra- red sensors by which I want to perceive the passage of a person through the door or his presence in the room. In addition it is necessary to take into consideration the other various situations that may occur when a person comes into the room or when he/she leaves. These situations can be in many cases similar, but the output should be able correctly distinguish the possibilites. The result of this effort is detector which is able to detect correctly one person or more people passing the door. People can browse through a door one behind the other, but they also can pass in the doorway in random combinations.

Triangle counting is a major graph problem with several applications in social network analysis, anomaly detection, etc. A considerable amount of work has contributed to approximately computing the global triangle counts using several computational models. One of the most popular streaming models considered is Edge Streaming in which the edges arrive in the form of a graph stream. We categorize the existing literature into two categories: Fixed Memory (FM) approach, and Fixed Probability (FP) approach. As the size of the graphs grows, several challenges arise such as memory space limitations, and prohibitively long running time. Therefore, both FM and FP categories exhibit some limitations. FP algorithms fail to scale for massive graphs. We identified a limitation of FM category $i.e.$ FM algorithms have higher computational time than their FP variants. In this work, we present a new category called the Hybrid approach that overcomes the limitations of both FM and FP approaches. We present two new algorithms that belong to the hybrid category: Neighbourhood Hybrid Multisampling (NHMS) and Triest/ThinkD Hybrid Sampling (THS) for estimating the number of global triangles in graphs. These algorithms are highly scalable and have better running time than FM and FP variants. We experimentally show that both NHMS and THS outperform state-of-the-art algorithms in space-efficient environments. / Graduate

Táto práca sa zaoberá redukciou veľkosti tzv. čítačových automatov. Čítačové automaty rozširujú klasické konečné automaty o čítače s obmedzeným rozsahom hodnôt. Umožňujú tým efektívne spracovať napr. regulárne výrazy s opakovaním: a{5,10}. V tejto práci sa zaoberáme reláciou simulácie v čítačových automatoch, pomocou ktorej sme schopní zredukovať ich veľkosť. Opierame sa pritom o klasickú simuláciu v konečných automatoch, ktorú netriviálnym spôsobom rozširujeme na čítačové automaty. Kľúčovým rozdielom je nutnosť simulovať okrem stavov taktiež čítače. Za týmto účelom zavádzame nový koncept parametrizovanej relácie simulácie, a navrhujeme metódy výpočtu tejto relácie a redukcie veľkosti čítačových automatov pomocou nej. Navrhnuté metódy sú tiež implementované a je vyhodnotená ich efektivita.

In this dissertation we consider the problem of cooperative sensing for secondary user access to primary user spectrum in cognitive radio systems. Using a fusion center or an access point, the cooperative users decide on the availability of spectrum for their use. Both Neyman-Pearson and Bayes criterion are considered for performance assessment. Our work on the asymptotic performance of counting rules with a very large number of sensors in decentralized detection problem shows that majority logic fusion rule has the same order of performance when compared to the best fusion rule based on the binary decisions received from the observing sensors in a network. In cognitive radio context, very large number of sensors may not be realistic and hence we would like to examine the performance of majority logic and counting rules involving a finite and small number of sensors. Uniformly most powerful test for decentralized detection for testing parameter θ when the observation is a sample from uniform (0,θ) distribution is investigated and it is shown that OR rule has the best performance among all counting rules in error free channel. The numerical study for reporting channel as a binary symmetric channel (BSC) with probability of bit error is also investigated and the results show that 2-out-of-5 or 2-out-of-10 has better performance among other k-out-of-n rules, whenever OR rule is not able to provide a probability of false alarm at the sensor, that lies over (0,1) at a given probability of bit error.

Predicting fatigue failure is a critical design element for many engineering components and structures subject to complex service conditions. In high-temperature and corrosive environments, many materials exhibit rate dependent phenomena that can significantly alter safe service life predictions. Existing cycle processing techniques such as Peak Counting, Simple Range, and the Rain Flow method are able to resolve complex service histories into sets of simple cycles, but these methods are unable to handle time-related parameters such as engage rate and cycle sequence. To address this, a cycle processor was written in FORTRAN 95 later termed the Multi-Algorithm Cycle Counter (MACC). This code was utilized as a platform to develop, test, and study various methods of extracting and interpreting rate parameters extracted from cycles defined by existing counting algorithms.

No description available.

Software designs consist of software components and their relationships. Graphs are abstraction of software designs. Graphs composed of nodes and hyperedges are attractive for depicting software designs. Measurement of abstractions quantify relationships that exist among components. Most conventional metrics are based on counting. In contrast, this work adopts information theory because design decisions are information. The goal of this research is to show that information theory-based metrics proposed by Allen, namely size, complexity, coupling, and cohesion, can be useful in real-world software development projects, compared to the counting-based metrics. The thesis includes three case studies with the use of global variables as the abstraction. It is observed that one can use the counting metrics for the size and coupling measures and the information metrics for the complexity and cohesion measures.