Improved Prediction-based Dynamic Load Balancing Systems for HLA-Based Distributed Simulations

Due to the dependency of High-Level Architecture (HLA)-Based simulations on the resources of distributed environments, simulations can face load imbalances and can suffer from low performance in terms of execution time. HLA is a framework that simplifies the implementation of distributed simulations; it also has been built with dedicated resources in mind. As technology is nowadays shifting towards shared environments, the following two weaknesses have become apparent in HLA: managing federates and reacting towards load imbalances on shared resources. Moreover, a number of dynamic load management systems have been designed in order to provide a solution to enable a balanced simulation environment on shared resources. These solutions use specific techniques depending on simulation characteristics or load aspects to perform the balancing task. Load prediction is one of such techniques that improves load redistribution heuristics by preventing load imbalances. In this thesis, a number of enhancements for a prediction technique are presented, and their efficiency are compared. The proposed enhancements solve the observed problems with Holt’s implementations on dynamic load balancing systems for HLA-Based distributed simulations and provide better forecasting. As a result, these enhancements provide better predictions for the load oscillations of the shared resources. Furthermore, a number of federate migration decision-making approaches are introduced to add more intelligence into the process of migrating federates. The approaches aim to solve a dependency problem in the prediction-based load balancing system on the prediction model, thus making similar systems adapt to any future system improvements

A data mining approach to improve the automated quality of data

This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data

The Effect of Brief Psychotherapy in Alleviating Anxiety and Depression in Cancer Patients Referred to a Psycho-oncology Clinic: Preliminary Study

This poster will present preliminary findings from a recent research study conducted at the George Washington University Medical Faculty Associates Department of Psychiatry. Psychological distress and morbidity (including loneliness, anxiety, depression and PTSD) may be triggered or exacerbated by cancer diagnosis (Swartzman, et al 2016). Depressed cancer patients show worse treatment adherence and worse survival compared with non-depressed cancer patients (Hartubf et al, 2017). Cancer survivors in the United States reported using medication for depression and anxiety at twice the rate of the general public (Hawkins et al 2017). Childhood cancer survivors may experience post-traumatic stress symptoms as young adults or adults. Psychiatrists and resident trainees are not normally trained to deal with special needs of cancer population, and this training takes place within the GW psychooncology clinic. Given the high prevalence of mood disorders and adjustment disorders among oncology patients, this study will aim to assess if our current intervention is beneficial in addressing the client’s target symptoms. The study will examine the effectiveness of brief psychotherapy for oncology patients. Currently, patients are referred to the psychooncology clinic from various oncologists and social workers with the oncology center. Resident psychiatrists provide 5-8 sessions of brief psychotherapy to address issues of anxiety, mood changes and adjustment to diagnosis. This study aims to examine if therapy sessions achieve the goal of helping to decrease anxiety and mood changes and changes patient’s outlook on life. Patients will be administered surveys assessing for depression, anxiety and well-being prior to and following therapy sessions and the results will be compared. The hypothesis is that patients will score significantly lower on the anxiety (GAD-7) and depression (PHQ-9) questionnaires and higher on the WHO 5 measure Quality of Life Scale, indicating that the several sessions of brief psychotherapy were effective in helping them to develop positive coping skills to adjust to their diagnosis and how it impacts their live

A decision table method for randomness measurement

Data quality has become a major concern for organisations. The rapid growth in the size and technology of a databases and data warehouses has brought significant advantages in accessing, storing, and retrieving information. At the same time, great challenges arise with rapid data throughput and heterogeneous accesses in terms of maintaining high data quality. Yet, despite the importance of data quality, literature has usually condensed data quality into detecting and correcting poor data such as outliers, incomplete or inaccurate values. As a result, organisations are unable to efficiently and effectively assess data quality. Having an accurate and proper data quality assessment method will enable users to benchmark their systems and monitor their improvement. This paper introduces a granules mining for measuring the random degree of error data which will enable decision makers to conduct accurate quality assessment and allocate the most severe data, thereby providing an accurate estimation of human and financial resources for conducting quality improvement tasks

[3+2] Cycloaddition Reaction for the Stereoselective Synthesis of a New Spirooxindole Compound Grafted Imidazo[2,1-b]thiazole Scaffold: Crystal Structure and Computational Study

A new spirooxindole hybrid engrafted imidazo[2,1-b]thiazole core structure was designed and achieved via [3+2] cycloaddition reaction approach. One multi-component reaction between the ethylene derivative based imidazo[2,1-b]thiazole scaffold with 6-Cl-isatin and the secondary amine under heat conditions afforded the desired compound in a stereoselective manner. The relative absolute configuration was assigned based on single-crystal X-ray diffraction analysis. Hirshfeld calculations for 4 revealed the importance of the H…H (36.8%), H…C (22.9%), Cl…H (10.4%) and S…H (6.6%), as well as the O…H (4.7%), N…H (5.3%), Cl…C (1.6%), Cl…O (1.0%) and N…O (0.5%) contacts in the crystal stability. DFT calculations showed excellent straight-line correlations (R2 = 0.9776–0.9962) between the calculated and experimental geometric parameters. The compound has polar nature (3.1664 Debye). TD-DFT and GIAO calculations were used to assign and correlate the experimental UV-Vis and NMR spectra, respectively