Parallel programming models are quite challenging and emerging topic in the parallel computing era. These models allow a developer to port a sequential application on to a platform with more number of processors so that the problem or application can be solved easily. Adapting the applications in this manner using the Parallel programming models is often influenced by the type of the application, the type of the platform and many others. There are several parallel programming models developed and two main variants of parallel programming models classified are shared and distributed memory based parallel programming models. The recognition of the computing applications that entail immense computing requirements lead to the confrontation of the obstacle regarding the development of the efficient programming models that bridges the gap between the hardware ability to perform the computations and the software ability to support that performance for those applications [25][9]. And so a better programming model is needed that facilitates easy development and on the other hand porting high performance. To answer this challenge this thesis confines and compares four different shared memory based parallel programming models with respect to the development time of the application under a shared memory based parallel programming model to the performance enacted by that application in the same parallel programming model. The programming models are evaluated in this thesis by considering the data parallel applications and to verify their ability to support data parallelism with respect to the development time of those applications. The data parallel applications are borrowed from the Dense Matrix dwarfs and the dwarfs used are Matrix-Matrix multiplication, Jacobi Iteration and Laplace Heat Distribution. The experimental method consists of the selection of three data parallel bench marks and developed under the four shared memory based parallel programming models considered for the evaluation. Also the performance of those applications under each programming model is noted and at last the results are used to analytically compare the parallel programming models. Results for the study show that by sacrificing the development time a better performance is achieved for the chosen data parallel applications developed in Pthreads. On the other hand sacrificing a little performance data parallel applications are extremely easy to develop in task based parallel programming models. The directive models are moderate from both the perspectives and are rated in between the tasking models and threading models. / From this study it is clear that threading model Pthreads model is identified as a dominant programming model by supporting high speedups for two of the three different dwarfs but on the other hand the tasking models are dominant in the development time and reducing the number of errors by supporting high growth in speedup for the applications without any communication and less growth in self-relative speedup for the applications involving communications. The degrade of the performance by the tasking models for the problems based on communications is because task based models are designed and bounded to execute the tasks in parallel without out any interruptions or preemptions during their computations. Introducing the communications violates the purpose and there by resulting in less performance. The directive model OpenMP is moderate in both aspects and stands in between these models. In general the directive models and tasking models offer better speedup than any other models for the task based problems which are based on the divide and conquer strategy. But for the data parallelism the speedup growth however achieved is low (i.e. they are less scalable for data parallel applications) are equally compatible in execution times with threading models. Also the development times are considerably low for data parallel applications this is because of the ease of development supported by those models by introducing less number of functional routines required to parallelize the applications. This thesis is concerned about the comparison of the shared memory based parallel programming models in terms of the speedup. This type of work acts as a hand in guide that the programmers can consider during the development of the applications under the shared memory based parallel programming models. We suggest that this work can be extended in two different ways: one is from the developer‘s perspective and the other is a cross-referential study about the parallel programming models. The former can be done by using a similar study like this by a different programmer and comparing this study with the new study. The latter can be done by including multiple data points in the same programming model or by using a different set of parallel programming models for the study. / C/O K. Manoj Kumar; LGH 555; Lindbloms Vägan 97; 37233; Ronneby. Phone no: 0738743400 Home country phone no: +91 9948671552

<div>As the number of Resident Space Objects around Earth continues to increase, the need for an optimal sensor tasking strategy, specifically with Ground-Based Optical sensors, continues to be of great importance. This thesis focuses on the single and multi-sensor tasking problem with realistic optical sensor modeling for the observation of objects in the Geosynchronous Earth Orbit regime. In this work, sensor tasking refers to assigning the specific?c observation times and viewing directions of a single or multi sensor framework to either survey for or track new or existing objects. For this work specifically, the sensor tasking problem will seek to maximize the total number of Geosynchronous Earth Orbiting objects to be observed from a catalog of existing objects with a single and multi optical sensor tasking framework. This research focuses on the physical assumptions and limitations on an optical sensor, and how these assumptions affect the single and multi sensor tasking scenario. First, the concept of the probability of detection of a resident space object is calculated based on the viewing geometry of the resident space object. Then, this probability of detection is compared to the system that avoids the computational process by implementing a classical heuristic minimum elevation constraint to an electro-optical charged coupled optical sensor. It is shown that in the single and multi-sensor tasking scenario if the probability of detection is not considered in the sensor tasking framework, then a rigid elevation constraint of around 25^o-35^o is recommended for tasking Geosynchronous objects. Secondly, the topic of complete geo-coverage within a single night is explored. A sensor network proposed by Ackermann et al. (2018) is studied with and without the probability of detection considerations, and with and without uncertainties in the resident space objects' states. (then what you have). For the multi-sensor system, it is shown that with the assumed covariance model for this work, the framework developed by Ackermann et al. (2018) does not meet the design requirements for the cataloged Geosynchronous objects from March 19th, 2019. Finally, the concept of a variable repositioning time for the slewing of the ground-based sensors is introduced and compared to a constant repositioning time model. A model for the variable repositioning time is derived from data retrieved from the Purdue Optical Ground Station. This model is applied to a single sensor scenario. Optimizers are developed using the two repositioning time functions derived in this work. It is shown that the constant repositioning models that are greater than the maximum repositioning time produce results close to the variable repositioning solution. When the optimizers are tested, it is shown that there is a small increase in performance only when the maximum repositioning time is significant.</div>

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Current studies done using a learning test for children have problems as they only make evaluations of Physically and Neurologically Impaired (PNI) children who can succeed in the test and can be considered as a PASS/FAIL test. This pilot study takes a holistic view of cognitive testing of PNI children using a user-test-device triad model and provides a framework using non-PNI children and adults as controls. Comparisons using adapted off-the-shelf novel interfaces to the computer, in particular, an Electroencephalograph (EEG) head-set, an eye-tracker and a head-tracker and a common mouse were carried out. In addition, two novel multi-modal technologies were developed based on the use of brain-waves and eye-tracking as well as head-tracking technologies to support the study. The devices were used on three tests with increasing cognitive complexity. A self-developed measure based on success streaks (consecutive outcomes) was introduced to improve evaluations of PNI children. A theoretical model regarding a fit of ability to devices was initially setup and finally modified to fit the view of the empirical model that emerged from the outcomes of the study. Results suggest that while multi-modal technologies can address weaknesses of the individual component modes, a compromise is made between the user’s ability for multi-tasking between the modes and the benefits of a multi-modal device but the sample size is very small. Results also show children failing a test with a mouse but passing it subsequently when direct communication is used suggesting that a device can affect a test for children who are of a developing age. This study provides a framework for a more meaningful conversation between educational psychologists as well as other professionals and PNI parents because it provides more discrimination of outcomes in cognitive tests for PNI children. The framework provides a vehicle that addresses scientifically the concerns of parents and schools.