Advanced Optimization Techniques For Monte Carlo Simulation On Graphics Processing Units

The objective of this work is to design and implement a self-adaptive parallel GPU optimized Monte Carlo algorithm for the simulation of adsorption in porous materials. We focus on Nvidia\u27s GPUs and CUDA\u27s Fermi architecture specifically. The resulting package supports the different ensemble methods for the Monte Carlo simulation, which will allow for the simulation of multi-component adsorption in porous solids. Such an algorithm will have broad applications to the development of novel porous materials for the sequestration of CO2 and the filtration of toxic industrial chemicals. The primary objective of this work is the release of a massively parallel open source Monte Carlo simulation engine implemented using GPUs, called GOMC. The code will utilize the canonical ensemble, and the Gibbs ensemble method, which will allow for the simulation of multiple phenomena, including liquid-vapor phase coexistence, and single and multi-component adsorption in porous materials. In addition, the grand canonical ensemble and the configurational-bias algorithms have been implemented so that polymeric materials and small proteins may be simulated. This simulation engine is the only open source GPU optimized Monte Carlo code available for the generalized simulation of adsorption and phase equilibria on a very large scale. As a result of conducting many optimization techniques and allowing the system to adjust for the change of simulation state, the original MC algorithm has been rewritten based on an existing serial algorithm to suit the massive parallel devices resulting in reductions in computational time. This large time reduction allow for the simulation of significantly larger systems for longer timescales than is currently possible with existing implementations. Results of the extensive research and applying device specific optimizations resulted in significant speedup. First, for the NVT method, a fully optimized serial algorithm has been implemented and the performance results has been compared to Towhee. A speedup of about 438 times has been achieved for a relatively small size problem of 4096 particles. In addition, two algorithms to run on the GPU with and without cell list structure have been implemented. The total speedup of the parallel code with cell list over the serial code was more than 160x faster. Moreover, for the grand canonical ensemble, a serial and two parallel algorithms have been developed. The simulation box in this method can be resized, which added a change to the algorithm that needed to adapt with the box size and adjust itself. The performance of running the CUDA code with cell list versus the serial code that doesn\u27t have a cell list structure is a factor of 130 times faster. More MC ensembles have been transferred to the GPU. The Gibbs ensemble method has two simulation boxes and three types of moves. This method has been studied carefully and the GPU algorithm has been implemented to port the computation intensive functions to the GPU. The performance of the GPU code was about 50x faster than the serial code. Finally, an extension of the Gibbs method has been implemented on the GPU. The particle transfer from one box to the other is the affected move type by this extension. CUDA streams are used to parallelize K trials for this method. A factor of three times speedup for the particle transfer move has been achieved for the best case. However, due to the low execution rate of the particle transfer move, just 10% of the total moves, the speedup has minimal effect on overall execution time of the simulation. Furthermore, a different run with all move types on Kepler K20c card has been executed, and a factor of 2 times speedup has been reported over the CUDA code on the GeForce GTX 480 card. The main contribution of this work to society is when the above implementations become open source to the public through http://gomc.eng.wayne.edu. Also, other researchers can take advantage of the lessons learned with advanced optimizations and self-adapting mechanisms specific to the GPU. On the application level, the current code can be used by the chemical engineering community to explore accurate and affordable simulations that were not possible before

Deep Learning Methods For Visual Object Recognition

Convolutional neural networks (CNNs) attain state-of-the-art performance on various classification tasks assuming a sufficiently large number of labeled training examples. Unfortunately, curating sufficiently large labeled training dataset requires human involvement, which is expensive, time-consuming, and susceptible to noisy labels. Semi-supervised learning methods can alleviate the aforementioned problems by employing one of two techniques. First, utilizing a limited number of labeled data in conjunction with sufficiently large unlabeled data to construct a classification model. Second, exploiting sufficiently large noisy label training data to learn a classification model. In this dissertation, we proposed a few new methods to mitigate the aforementioned problems. We summarize our main contributions in three main facets describe below. First, we presented anew Hybrid Residual Network Method (HyResNet) that exploits the power of both supervised and unsupervised deep learning methods into a single deep supervised learning model. Our experiments show the efficacy of HyResNet on visual object recognition tasks. We tested HyResNet on benchmark datasets with various configurations and settings. HyResNet showed comparable results to the state-of-the-art methods on the benchmark datasets. Second, we proposed a deep semi-supervised learning method (DSSL). DSSL utilizes both supervised and unsupervised neural networks. The novelty of DSSL originates from its nature in employing a limited number of labeled training examples in conjunction with sufficiently large unlabeled examples to create a classification model. The combination of DSSL architecture and self-training has a joint impact on the performance over the DSSL. We measured the performance of DSSL method on five benchmark datasets with various labeled / unlabeled levels of training examples and then compared our results with state-of-the-art methods. The experiments show that DSSL sets a new state-of-the-art record for various benchmark tasks. Finally, we introduced a new teacher/student semi-supervised deep learning methods (TS-DSSL). TS-DSSL accepts an input of noisy label training dataset then it employs a self-training and self-cleansing techniques to train a deep learning model. The integration of TS-DSSL architecture with the training protocol maintain the stability of the model and enhance the overall model performance. We evaluated the performance of TS-DSSL on benchmark semi-supervised learning tasks with different levels of noisy labels synthesized from different noise distributions. The experiments showed that TS-DSSL sets a new state-of-the-art record on the benchmark tasks

An Efficient Cell List Implementation for Monte Carlo Simulation on GPUs

Maximizing the performance potential of the modern day GPU architecture requires judicious utilization of available parallel resources. Although dramatic reductions can often be obtained through straightforward mappings, further performance improvements often require algorithmic redesigns to more closely exploit the target architecture. In this paper, we focus on efficient molecular simulations for the GPU and propose a novel cell list algorithm that better utilizes its parallel resources. Our goal is an efficient GPU implementation of large-scale Monte Carlo simulations for the grand canonical ensemble. This is a particularly challenging application because there is inherently less computation and parallelism than in similar applications with molecular dynamics. Consistent with the results of prior researchers, our simulation results show traditional cell list implementations for Monte Carlo simulations of molecular systems offer effectively no performance improvement for small systems [5, 14], even when porting to the GPU. However for larger systems, the cell list implementation offers significant gains in performance. Furthermore, our novel cell list approach results in better performance for all problem sizes when compared with other GPU implementations with or without cell lists.Comment: 30 page

Bioavailability and Pharmacokinetics Studies of Gamma Oryzanol

Rice bran oil was extracted from rice bran collected after four milling breaks that were used to process rice in Bernas factory, Sekinchan, Malaysia. Two organic solvents were used, a non-polar solvent that was hexane and a mixture of non-polar and polar, which were chloroform-methanol. Gamma oryzanol content of rice bran oil was then quantified, and the total antioxidant activity (TAA) was determined using FTC and TBA methods. After oil extraction, dietary fiber content was quantified in the four phases of defatted rice bran. Results showed that rice bran contained around 20 % lipid in the extracts of the two solvents used. Unlike oil yield, y-oryzanol content was affected by rice milling and the type of solvent used for extraction. For chloroform-methanol extract, phase 2 of rice milling contained the highest amount of y-oryzanol (5280 * 120 pprn), followed by phase 3 (3820 * 60 pprn), phase 4 (3400 * 100 pprn), and phase 1 (3000 * 80 pprn). The four phases of hexane extracts contained lower amount of yoryzanol than chloroform-methanol extracts. Phase 2 of rice milling contained the highest y-oryzanol content (4560 100 pprn), followed by phase 3 (2400 * 40 pprn),. phase 4 (2080 * 40 pprn), and phase 1 (1600 * 60 pprn). TAA studies showed that rice bran oil extracted from phase 2 of rice milling had significantly higher antioxidant activity than phase 1 (pc0.05). However, no significant differences were found among other phases (p0.05). It was found that rice bran is a good source of dietary fiber. However, fiber distribution was affected also by milling systems. Phase 2 of rice milling contained the highest amount of TDF which was 5 1.2 * 0.9 %, followed by phases 3, 1 and 4 that contained 45.2 * 1.0 %, 37.6 * 0.1 % and 35.5 * 0.8 % respectively. Caco-2 cell line was used as in vitro model to study y-oryzanol bioavailability from different formulations that were triolein solution, emulsion, tocotrienol rich fraction (TRF)-y-oryzanol emulsion, and microspheres. By day 9, cell line showed polarized monolayer properties as was detected from transepithelial electrical resistance (TEER) value (247.2 * 25.0 &m2) and phenol red diffusion (4.2 + 0.1 %). However, all experiments were conducted at day 18, to ensure that cells were fully polarized. In vitro digestion of 100 mg dose from each formulation resulted in low micellarization concentrations of y-oryzanol from both triolein solution and microspheres, that were 2 1 * 2 pglml digestate, and 20 * 2 pgml respectively. Nevertheless, micellarization concentrations were greatly improved to 5087 * 147 pglml and 5 160 + 228 pglml, from emulsion and TRF- y-oryzanol emulsion, respectively. After 10 h of incubation, only 0.43 * 0.02 pg (2.03 +_ 0.09 %) y-oryzanol was transported to the lower compartments from triolein solution. Cellular uptake of y-oryzanol from microspheres after the same period of incubation, increased to 1.25 * 0.09 pg (6.33 f 0.44 %). Gamma oryzanol absorption increased further to 1 14.94 * 2.02 pg (2.3 1 f 0.04 %) and 1 15.82 * 4.52 pg (2.24 + 0.05 %) from emulsion and TRF- y-oryzanol emulsion, respectively. Phannacokinetics of y-oryzanol was studied using rabbits. Gamma oryzanol emulsion was given as a single intravenous dose. Plasma level of y-oryzanol was quantified using HPLC. Plasma clearance of y-oryzanol followed two compartments model, indicating that y-oryzanol was distributed to the internal tissues. Elimination constant was 0.086 * 0.004 pg/ml.h, and the half-life was 8.040 * 0.360 h. Rabbits were used as in vivo model to study the bioavailability of y-oryzanol from triolein solution, microspheres, emulsion and TRF- y-oryzanol emulsion. The maximum concentration of y-oryzanol from triolein solution was 6.37 * 1.48 pg/ml, and improved to 130.30 * 30.40 pglml upon loading y-oryzanol in microspheres. However, in both formulations, the maximum concentrations were achieved after 2 h of ingestion. Where as the maximum concentrations of y-oryzanol from emulsion and TRF- y-oryzanol emulsion were 555 * 100 pglml and 525 * 95 pglml respectively and the t max. was 2 h. The absolute bioavailability of y-oryzanol emulsion was 6.61 * 0.86 %. The oral emulsion was used as a standard, so that the relative bioavailabilitiy (F relative) values of the other formulations were calculated. While F( relative) for y-oryzanol from triolein solution was only 0.51 * 0.06 %, it was significantly ('<0.05) increased to 16.63 * 1.71 % upon loading y-oryzanol in microspheres. Addition of TRF to y-oryzanol emulsion resulted in an increase of F (relative) to 109.60 * 13.83 %. However, this increase could be due to the preservative effect of TRF antioxidants. In conclusion, the bioavailability of y-oryzanol was low. However, its absorption increased around 200 times after emulsification and 33 times upon loading in microspheres

University students' readiness for the national workforce : a study of vocational identity and career decision-making

The purpose of this study was to determine the level of vocational identity and career decision status of students at the Hashemite University which was assumed to be an indication of their readiness for the national workforce in Jordan. A total of 641 students participated in the study by completing the ‘Vocational Identity Scale’ (VIS) and the ‘Career Decision Scale’ (CDS) selected for the study. The results indicated that students have a high sense of vocational identity and greater career decidedness as represented by their overall mean values. Furthermore, there were no significant differences among university students in perceiving the VIS and CDS that are attributed to their gender and academic standing. However, differences on the VIS and CDS were found that are attributed to type of faculty. The study concludes by offering a number of theoretical and practical implications for the field of career and vocational development.peer-reviewe

The influence of consumer misbehaviour on the perceived brand image of Jordanian Higher Education Institutions

Higher education institutions are working hard to associate their names with a positivebrand image. However, an increasing phenomenon significantly affecting JordanianUniversities is campus violence perpetrated by consumer misbehaviour. Consumermisbehaviour in higher education has not been adequately researched and the incidencesof campus violence are under reported by actors, and acted upon by the authorities. As,there is no single study in Jordan that has tackled campus violence from a marketingperspective, this thesis aims to explore the influence of consumer misbehaviour oninternational students’ perspective of Jordanian Higher Education Institutions’ (JHEIs)brand image. For reasons of clarity and international theoretical relevance, this thesisadopts the international term “consumer misbehaviours” in referring to the phenomenonof campus violence in JHEIs. Qualitative empirical semi-structured interviews withvarious international students were conducted in four Jordanian universities in order togain an in-depth understanding of the phenomena and its influence on the brand imageof JHEIs. This study revealed the prevalence of consumer misbehaviours and theirconsequences for JHEIs. The findings revealed multiple drivers of consumermisbehaviours, for example personal, cultural norms, academic, political, economic,and institutional. Furthermore, the types of consumer misbehaviours revealed, includedverbal and psychological abuse, physical assault, sexual harassment, property damage,tribal brawls, discrimination and racism. Moreover, consumer misbehaviours werefound to have a negative influence on the international brand image of Jordanian HigherEducation (JHE), which subsequently affects the Jordanian economy. Despite this, thefindings also showed that consumer misbehaviours are not always negative. Forexample, fighting against the injustices of universities’ policies, and forcing institutionsto employ more security and qualified staff. The outcomes of this study generatenumerous implications and suggestions for theorists and practitioners in the educationalmarketing field in order to mitigate student consumer misbehaviours. Higher educationinstitutions can use the results of this study to make the educational environment safer,correct weaknesses identified by this study and develop policies, which will improve thesafety of customers and staff. Examples of such policies include: engagement andcollaboration, encouragement of good conduct, and increase collaborations with all HEstakeholders etc. Accordingly, the results provide a foundation on which future researchcan be built

Efficient removal of phenol compounds from water environment using Ziziphus leaves adsorbent

© 2020 Elsevier B.V. Industrial processes generate toxic organic molecules that pollute environment water. Phenol and its derivative are classified among the major pollutant compounds found in water. They are naturally found in some industrial wastewater effluents. The removal of phenol compounds is therefore essential because they are responsible for severe organ damage if they exist above certain limits. In this study, ground Ziziphus leaves were utilized as adsorbents for phenolic compounds from synthetic wastewater samples. Several experiments were performed to study the effect of several conditions on the capacity of the Ziziphus leaves adsorbent, namely: the initial phenol concentration, the adsorbent concentration, temperature, pH value, and the presence of foreign salts (NaCl and KCl). The experimental results indicated that the adsorption process reached equilibrium in about 4 h. A drop in the amount of phenol removal, especially at higher initial concentration, was noticed upon increasing the temperature from 25 to 45 °C. This reflects the exothermic nature of the adsorption process. This was also confirmed by the calculated negative enthalpy of adsorption (−64.8 kJ/mol). A pH of 6 was found to be the optimum value at which the highest phenol removal occurred with around 15 mg/g at 25 °C for an initial concentration of 200 ppm. The presence of foreign salts has negatively affected the phenol adsorption process. The fitting of the experimental data, using different adsorption isotherms, indicated that the Harkins-Jura isotherm model was the best fit, evident by the high square of the correlation coefficient (R2) values greater than 0.96. The kinetic study revealed that the adsorption was represented by a pseudo-second-order reaction. The results of this study offer a basis to use Ziziphus leaves as promising adsorbents for efficient phenol removal from wastewater

Promoting border areas for developmental ecotourism: A case study of Al-Adaseya, Jordan

Beyond the ecological perspective of this study, the participatory tourism planning project to spread the economic benefits in term of community-based ecotourism development in the northern border periphery of Al-Adaseya, Jordan is discussed. In such a context of peripheral developmental border areas, where wars and immigration shapes new geopolitical situations, developmental ecotourism projects can be a key to establish small scale business, and thus improve the lives of both locals and those across-borders. Such projects also, provide unique ecological systems for tourists, and maximise the cultural value among people. The study examines the potentials and limitations of tourism for domestic and cross border mergers in Al-Adaseya, and develops suggestions for the promoting of small scale tourism in such rural areas, with regard to the various cross cultural aspect of locals. The study was mainly descriptive and adopted a methodology based exclusively on-site visit observations, combined with face-to-face interviews. The research findings indicate that even though the region hosts considerable natural and cultural resources, it is faced with different obstacles that impact the development of ecotourism, related mainly to the particular security situation for its strategically tricky location when it comes to regional instability and a volatile political situation. Strategic factors were explored and priorities set out in this study in order to address the problems of the region. Rehabilitating historical houses, improving infrastructure, and tourism facilities were also included in the recommendations