Learning Robust Support Vector Machine Classifiers With Uncertain Observations

The central theme of the thesis is to study linear and non linear SVM formulations in the presence of uncertain observations. The main contribution of this thesis is to derive robust classfiers from partial knowledge of the underlying uncertainty. In the case of linear classification, a new bounding scheme based on Bernstein inequality has been proposed, which models interval-valued uncertainty in a less conservative fashion and hence is expected to generalize better than the existing methods. Next, potential of partial information such as bounds on second order moments along with support information has been explored. Bounds on second order moments make the resulting classifiers robust to moment estimation errors. Uncertainty in the dataset will lead to uncertainty in the kernel matrices. A novel distribution free large deviation inequality has been proposed which handles uncertainty in kernels through co-positive programming in a chance constraint setting. Although such formulations are NP hard, under several cases of interest the problem reduces to a convex program. However, the independence assumption mentioned above, is restrictive and may not always define a valid uncertain kernel. To alleviate this problem an affine set based alternative is proposed and using a robust optimization framework the resultant problem is posed as a minimax problem. In both the cases of Chance Constraint Program or Robust Optimization (for non-linear SVM), mirror descent algorithm (MDA) like procedures have been applied

Abdellatif Laâbi’s Casablanca Spleen

In January 1972, the thirty-year old Moroccan poet Abdellatif Laâbi was arrested by his country’s security services and brutally tortured. Student demonstrations in his support ensued, which eventually forced the authorities to release him, only to re-arrest him a month later, when he was sent to Casablanca’s Moulay Cherif Detention Centre. Originally detained without being charged, Laâbi took part in a series of hunger strikes alongside other prisoners before finally being granted a trial in August 1973, at which point he was condemned to an eight and half year sentence at the infamous Kénitra penitentiary. His crime? Distributing political pamphlets. During his stay in Kénitra as prisoner number 18611, Laâbi would produce a body of work that would later be recognized as some of the twentieth century’s finest political poetry, alongside that of Pablo Neruda and Nâzım Hikmet

Study of the trajectories of ice shed by deicing system around aircraft engine

The problem of ice accretion caused accidents and incidents to aircraft over the past decades. Solving the problem of ice accretion employing de-icing and anti-icing devices will remove the accumulated ice but the problem of unknown trajectories of the detached particles appears. The flown particles represent a great hazard on the aircraft which yields risk depending on the vulnerability of aircraft parts. The vulnerable aircraft parts are the wing, the rear fuselage, the stabilizers, and the rear-mounted engines. In order to mitigate the risk, a study of the trajectories of those particles is introduced. The objective of this research is to study the trajectories around a wing by changing the angle of attack and the sweepback angle. The goal is to calculate the minimal number of ice trajectories to correctly predict a footprint map at the inlet section of the engine using the Monte-Carlo method. A numerical approach is used to accomplish this study. The random trajectories of the ice particles are calculated using a 3D Panel Method (3DPM) flow field around the wing. To determine the zones behind the wing where the ice particles have the most passage probability, a Monte-Carlo method is utilized. In this research, the calculations are done through a probabilistic study of the footprints to determine their probability distribution's shape. Once the shape is known, a normality test is done on the shape of the Probability Distribution Function (PDF) called the Kolmogorov-Smirnov test. After determining the shape and the type of the PDFs, a study on the mean and variance for every PDF is done to check the minimal number of trajectories to fulfill the Monte-Carlo method. The 3DPM flow field is validated against the literature as well as the footprint distribution behind the wing. The effect of the angle of attack, as well as the sweepback angle on ice particle trajectories, is shown. The increase of the angle of attack shifts the trajectories upward while the sweepback makes the footprint map less noisy. Finally, 500 trajectories were found enough to predict a footprint map

Effect of Solanum melongena peel extract in the treatment of arsenical keratosis

This study was conducted to examine the effect of the ointment containing Solanum melongena peel extract in the treatment of arsenical keratosis. In total, 23 patients were enrolled on the basis of inclusion and exclusion criteria. The ointment was given to each patient and advised him/her to apply to the site of lesion twice daily for 12 weeks without any gap. The size of the lesion and its photograph were collected before and at the end of the study. The mean (± SD) diameter of the lesion was 3.9 ± 2.1 cm which reduced to 1.8 ± 1.3 cm (reduction 54%). The results were statistically significant.  In conclusion, S. melongena peel extract is found to be effective in the treatment of arsenical keratosis

Effect of Solanum melongena peel extract in the treatment of arsenical keratosis

This study was conducted to examine the effect of the ointment containing Solanum melongena peel extract in the treatment of arsenical keratosis. In total, 23 patients were enrolled on the basis of inclusion and exclusion criteria. The ointment was given to each patient and advised him/her to apply to the site of lesion twice daily for 12 weeks without any gap. The size of the lesion and its photograph were collected before and at the end of the study. The mean (± SD) diameter of the lesion was 3.9 ± 2.1 cm which reduced to 1.8 ± 1.3 cm (reduction 54%). The results were statistically significant.  In conclusion, S. melongena peel extract is found to be effective in the treatment of arsenical keratosis

Historical trends of the professional improvement of the doctor in primary health care for the early diagnosis of alterations in oral comunication

Introduction: oral communication (OC) disorders as a health problem constitute a starting point for the design of professional development of professionals working at the Primary Health Care (PHC) level. Objective: to characterize the historical tendencies of professional development of physicians in PHC for the early diagnosis of OC disorders. Methods: the dialectic method was used as the guiding method. At the theoretical level: historical-logical, analytical-synthetic and inductive-deductive. From the empirical level: documentary review. Results: as national tendencies of the professional improvement of the physician in PHC for the early diagnosis of OC alterations were found in this research: the professional improvement of the Comprehensive General Practitioner (MGI) in relation to OC disorders and their early diagnosis has not been identified as a learning need; recognition of the importance of the MGI in the early detection of OC disorders, according to national demands; and the demands of a professional improvement in relation to OC disorders that enhances the real scenarios where child care is performed and prioritizes the participation of the MGI. Conclusions: in correspondence with the international tendencies of postgraduate studies, as a strategic development instrument, the professional improvement of physicians in PHC for the early diagnosis of OC disorders shows tendencies that are oriented to the professional improvement and to the quality of life of the population

Biobeneficiation of bauxite ore through bacterial desilication

ABSTRACT Bauxite is an important mineral ore that is widely used in aluminum industry for metallurgical and refractory purposes. However bauxite contains silica as an impurity which degrades its quality. Silica forms complex with the caustic used during the processing of ore thereby forming precipitates. This leads to unnecessary wastage of caustic that contributes to the higher processing costs. Moreover, the use of excess caustic to neutralize the reactive silica during the process increases the alkalinity of the waste product so called red mud which imposes severe disposal problem. Therefore, the removal of silica from bauxite ore by a feasible and environmental friendly method is of paramount importance. The current study focuses on the beneficiation of low quality bauxite ores, through the process of bioleaching of silica. Bacterial desilication was carried out using indigenous bacterial cultures isolated from the ore. Bacterial colonies were successfully isolated and potential silica leaching strains was screened. Various process parameters such as pH, temperature, aeration time, inoculum size, age of the inoculum and bauxite percentage were studied through Taguchi method for process optimization. Optimum conditions for bioleaching of silica were obtained as pH 7.5, temperature 25ºC, initial aeration time of 30 minutes, bauxite percentage of 5% using 48 hours old 5% inoculums were established by Taguchi method,. Furthermore, optimum process conditions were used for bioleaching of silica under for different lengths of time i.e. 5, 15, 20, 25 days. Biological leaching results showed a maximum of 41% silica was recovered at the end of 25 days. Further, biochemical characterization of the potential bacterial culture proved it to be of Bacillus sp

How Do Therapists Understand and Intend to Implement Practice Guideline Recommendations for Rehabilitation of the Upper Limb Following Stroke?

Stroke rehabilitation interventions must be evidence-based and applicable to a range of stroke subtypes and severity of disabilities to obtain the optimal outcomes. Clinical practice guidelines assist clinicians to implement rehabilitation plans based on research evidence. Evaluations of clinicians’ practices suggest that therapists may not be following guidelines, which may explain why patient outcomes are less than expected. To increase therapists' adherence to guidelines, it would help to understand their understanding, barriers and facilitators to implementing a clinical guideline. The purpose of this thesis was to demonstrate how rehabilitation therapists understand and interpret specific clinical guideline recommendations for upper limb rehabilitation post-stroke, and to identify perceived implementation barriers and facilitators. This thesis has two elements. The first demonstrates the application of the Theory of Planned Behaviour as a conceptual framework for understanding rehabilitation professionals’ intention toward implementation of clinical guidelines in rehabilitation of persons following stroke. The second part illustrates how physiotherapists and occupational therapists understand the individual recommendations for rehabilitation of upper extremity after stroke from the Canadian Best Practice Recommendations for Stroke Care. It also characterizes the barriers and facilitators that influence therapists’ uptake of these recommendations. The data for second manuscript were collected from therapists in two different countries (Canada and Saudi Arabia) to explore the global issues of clinical guidelines implementation. The review of the Theory of Planned Behaviour informed the study design and thinking about barriers and facilitators; but thematic analyses were driven by the data, not by theory. The similarities across health systems in the two countries were more striking than the differences, highlighting common challenges for guideline implementation. The findings of this thesis highlight the need for clearer communication of the specific actions intended by the CPG, and education of therapists to ensure they know how to implement interventions utilizing these specific actions.ThesisMaster of Science (MSc

Learning Robust Support Vector Machine Classifiers With Uncertain Observations

The central theme of the thesis is to study linear and non linear SVM formulations in the presence of uncertain observations. The main contribution of this thesis is to derive robust classfiers from partial knowledge of the underlying uncertainty. In the case of linear classification, a new bounding scheme based on Bernstein inequality has been proposed, which models interval-valued uncertainty in a less conservative fashion and hence is expected to generalize better than the existing methods. Next, potential of partial information such as bounds on second order moments along with support information has been explored. Bounds on second order moments make the resulting classifiers robust to moment estimation errors. Uncertainty in the dataset will lead to uncertainty in the kernel matrices. A novel distribution free large deviation inequality has been proposed which handles uncertainty in kernels through co-positive programming in a chance constraint setting. Although such formulations are NP hard, under several cases of interest the problem reduces to a convex program. However, the independence assumption mentioned above, is restrictive and may not always define a valid uncertain kernel. To alleviate this problem an affine set based alternative is proposed and using a robust optimization framework the resultant problem is posed as a minimax problem. In both the cases of Chance Constraint Program or Robust Optimization (for non-linear SVM), mirror descent algorithm (MDA) like procedures have been applied